Search results for: ISAR imaging

Authors: Chung-Hyeon Ryu, Do-Hyoung Kim, Hak-Sung Kim

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As the use of the composites was increased, the detecting method of hidden damages which have an effect on performance of the composite was important. Terahertz (THz) spectroscopy was assessed as one of the new powerful nondestructive evaluation (NDE) techniques for fiber reinforced composite structures because it has many advantages which can overcome the limitations of conventional NDE techniques such as x-rays or ultrasound. The THz wave offers noninvasive, noncontact and nonionizing methods evaluating composite damages, also it gives a broad range of information about the material properties. In additions, it enables to detect the multiple-delaminations of various nonmetallic materials. In this study, the pulse type THz spectroscopy imaging system was devised and used for detecting and evaluating the hidden delamination in the glass fiber reinforced plastic (GFRP) composite laminates. The interaction between THz and the GFRP composite was analyzed respect to the type of delamination, including their thickness, size and numbers of overlaps among multiple-delaminations in through-thickness direction. Both of transmission and reflection configurations were used for evaluation of hidden delaminations and THz wave propagations through the delaminations were also discussed. From these results, various hidden delaminations inside of the GFRP composite were successfully detected using time-domain THz spectroscopy imaging system and also compared to the results of C-scan inspection. It is expected that THz NDE technique will be widely used to evaluate the reliability of composite structures.

Keywords: terahertz, delamination, glass fiber reinforced plastic composites, terahertz spectroscopy

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Authors: Giselle Tran, Ralitza Parina, Phuong T. Nguyen

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Background/Aims: Pancreatic cysts (PC) have recently become an increasingly common entity, often diagnosed as incidental findings on cross-sectional imaging. Clinically, management of the lesions is difficult because of uncertainties in their potential for malignant degeneration. Prior series have reported that carcinoembryonic antigen (CEA), a biomarker collected from cyst fluid aspiration, has a high diagnostic accuracy for discriminating between mucinous and non-mucinous lesions, at the patient’s initial presentation. To the author’s best knowledge, no prior studies have reported PC CEA levels obtained from endoscopic ultrasound fine-needle aspiration (EUS-FNA) over years of serial EUS surveillance imaging. Methods: We report a consecutive retrospective series of 624 patients who underwent EUS evaluation for a PC between 11/20/2009 and 11/13/2018. Of these patients, 401 patients had CEA values obtained at the point of entry. Of these, 157 patients had two or more CEA values obtained over the course of their EUS surveillance. Of the 157 patients (96 F, 61 M; mean age 68 [range, 62-76]), the mean interval of EUS follow-up was 29.7 months [3.5-128]. The mean number of EUS procedures was 3 [2-7]. To assess CEA value fluctuations, we defined an appreciable increase in CEA as "spikes" – two-times increase in CEA on a subsequent EUS-FNA of the same cyst, with the second CEA value being greater than 1000 ng/mL. Using this definition, cysts with a spike in CEA were compared to those without a spike in a bivariate analysis to determine if a CEA spike is associated with poorer outcomes and the presence of high-risk features. Results: Of the 157 patients analyzed, 29 had a spike in CEA. Of these 29 patients, 5 had a cyst with size increase >0.5cm (p=0.93); 2 had a large cyst, >3cm (p=0.77); 1 had a cyst that developed a new solid component (p=0.03); 7 had a cyst with a solid component at any time during surveillance (p=0.08); 21 had a complex cyst (p=0.34); 4 had a cyst categorized as "Statistically Higher Risk" based on molecular analysis (p=0.11); and 0 underwent surgical resection (p=0.28). Conclusion: With serial EUS imaging in the surveillance of PC, an increase in CEA level defined as a spike did not predict poorer outcomes. Most notably, a spike in CEA did not correlate with the number of patients sent to surgery or patients with an appreciable increase in cyst size. A spike in CEA did not correlate with the development of a solid nodule within the PC nor progression on molecular analysis. Future studies should focus on the selected use of CEA analysis when patients undergo EUS surveillance evaluation for PCs.

Keywords: carcinoembryonic antigen (CEA), endoscopic ultrasound (EUS), fine-needle aspiration (FNA), pancreatic cyst, spike

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Authors: Bakhtiar Azadbakht, Karim Adinehvand, Amin Sahebnasagh

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The purpose of this study was to evaluate dependence of PAGAT polymer gel dosimeter 1/T2 on different electron and photon energies as well as on different mean dose rates for a standard clinically used Co-60 therapy unit and an ELECTA linear accelerator. A multi echo sequence with 32 equidistant echoes was used for the evaluation of irradiated polymer gel dosimeters. The optimal post-manufacture irradiation and post imaging times were both determined to be one day. The sensitivity of PAGAT polymer gel dosimeter with irradiation of photon and electron beams was represented by the slope of calibration curve in the linear region measured for each modality. The response of PAGAT gel with photon and electron beams is very similar in the lower dose region. The R2-dose response was linear up to 30Gy. In electron beams the R2-dose response for doses less than 3Gy is not exact, but in photon beams the R2-dose response for doses less than 2Gy is not exact. Dosimeter energy dependence was studied for electron energies of 4, 12 and 18MeV and photon energies of 1.25, 4, 6 and 18MV. Dose rate dependence was studied in 6MeV electron beam and 6MV photon beam with the use of dose rates 80, 160, 240, 320, 400, and 480cGy/min. Evaluation of dosimeters were performed on Siemens Symphony, Germany 1.5T Scanner in the head coil. In this study no trend in polymer-gel dosimeter 1/T2 dependence was found on mean dose rate and energy for electron and photon beams.

Keywords: polymer gels, PAGAT gel, electron and photon beams, MRI

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Authors: Yifan Lu, Ying Cui, Ying Zhu, Edward S. Lu, Rebecca Zeng, Rohan Bajaj, Raviv Katz, Rongrong Le, Jay C. Wang, John B. Miller

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Purpose: Retinal artery occlusion (RAO) is an ophthalmic emergency that can lead to poor visual outcome and is associated with an increased risk of cerebral stroke and cardiovascular events. Fluorescein angiography (FA) is the traditional diagnostic tool for RAO; however, wide-field swept-source optical coherence tomography angiography (WF SS-OCTA), as a nascent imaging technology, is able to provide quick and non-invasive angiographic information with a wide field of view. In this study, we looked for associations between OCT-A vascular metrics and visual acuity in patients with prior diagnosis of RAO. Methods: Patients with diagnoses of central retinal artery occlusion (CRAO) or branched retinal artery occlusion (BRAO) were included. A 6mm x 6mm Angio and a 15mm x 15mm AngioPlex Montage OCT-A image were obtained for both eyes in each patient using the Zeiss Plex Elite 9000 WF SS-OCTA device. Each 6mm x 6mm image was divided into nine Early Treatment Diabetic Retinopathy Study (ETDRS) subfields. The average measurement of the central foveal subfield, inner ring, and outer ring was calculated for each parameter. Non-perfusion area (NPA) was manually measured using 15mm x 15mm Montage images. A linear regression model was utilized to identify a correlation between the imaging metrics and visual acuity. A P-value less than 0.05 was considered to be statistically significant. Results: Twenty-five subjects were included in the study. For RAO eyes, there was a statistically significant negative correlation between vision and retinal thickness as well as superficial capillary plexus vessel density (SCP VD). A negative correlation was found between vision and deep capillary plexus vessel density (DCP VD) without statistical significance. There was a positive correlation between vision and choroidal thickness as well as choroidal volume without statistical significance. No statistically significant correlation was found between vision and the above metrics in contralateral eyes. For NPA measurements, no significant correlation was found between vision and NPA. Conclusions: This is the first study to our best knowledge to investigate the utility of WF SS-OCTA in RAO and to demonstrate correlations between various retinal vascular imaging metrics and visual outcomes. Further investigations should explore the associations between these imaging findings and cardiovascular risk as RAO patients are at elevated risk for symptomatic stroke. The results of this study provide a basis to understand the structural changes involved in visual outcomes in RAO. Furthermore, they may help guide management of RAO and prevention of cerebral stroke and cardiovascular accidents in patients with RAO.

Keywords: OCTA, swept-source OCT, retinal artery occlusion, Zeiss Plex Elite

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Authors: Suhas Pednekar, Prashant Chavan, Ramesh Chaughule, Deepak Patkar

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Iron oxide (Fe3O4) magnetic nanoparticles (MNPs) are one of the most attractive nanomaterials for various biomedical applications. An important potential medical application of polymer-coated iron oxide nanoparticles (NPs) is as imaging agents. Composition, size, morphology and surface chemistry of these nanoparticles can now be tailored by various processes to not only improve magnetic properties but also affect the behavior of nanoparticles in vivo. MNPs are being actively investigated as the next generation of magnetic resonance imaging (MRI) contrast agents. Also, there is considerable interest in developing magnetic nanoparticles and their surface modifications with therapeutic agents. Our study involves the synthesis of biocompatible cancer drug coated with iron oxide nanoparticles and to evaluate their efficacy as MRI contrast agents. A simple and rapid microwave method to prepare Fe3O4 nanoparticles has been developed. The drug was successfully conjugated to the Fe3O4 nanoparticles which can be used for various applications. The relaxivity R2 (reciprocal of the spin-spin relaxation time T2) is an important factor to determine the efficacy of Fe nanoparticles as contrast agents for MRI experiments. R2 values of the coated magnetic nanoparticles were also measured using MRI technique and the results showed that R2 of the Fe complex consisting of Fe3O4, polymer and drug was higher than that of bare Fe nanoparticles and polymer coated nanoparticles. This is due to the increase in hydrodynamic sizes of Fe NPs. The results with various amounts of iron molar concentrations are also discussed. Using MRI, it is seen that the R2 relaxivity increases linearly with increase in concentration of Fe NPs in water.

Keywords: cancer drug, hydrodynamic size, magnetic nanoparticles, MRI

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Authors: Ademuyiwa Agbonyin, Stamatis Zoras, Mohammad Zandi

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This paper investigates the extent to which building energy modelling can be informed based on preliminary information provided by infrared thermography using a thermal imaging camera in a walkthrough audit. The case-study building is the Sheffield Cathedral, built in the early 1400s. Based on an informative qualitative report generated from the thermal images taken at the site, the regions showing significant heat loss are input into a computer model of the cathedral within the integrated environmental solution (IES) virtual environment software which performs an energy simulation to determine quantitative heat losses through the building envelope. Building data such as material thermal properties and building plans are provided by the architects, Thomas Ford and Partners Ltd. The results of the modelling revealed the portions of the building with the highest heat loss and these aligned with those suggested by the thermal camera. Retrofit options for the building are also considered, however, may not see implementation due to a desire to conserve the architectural heritage of the building. Results show that thermal imaging in a walk-through audit serves as a useful guide for the energy modelling process. Hand calculations were also performed to serve as a 'control' to estimate losses, providing a second set of data points of comparison.

Keywords: historic buildings, energy retrofit, thermal comfort, software modelling, energy modelling

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Authors: Christian Skowronski, Andrew Shanholtzer, Brent Yelton, Muayad Almahariq, Daniel J. Krauss

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Prostate cancer has the third highest incidence rate and is the second leading cause of cancer death for men in the United States. Of the diagnostic tools available for intermediate-risk prostate cancer, magnetic resonance imaging (MRI) provides superior soft tissue delineation serving as a valuable tool for both diagnosis and treatment planning. Currently, there is minimal data regarding the practical utility of MRI for evaluation of intermediate-risk prostate cancer. As such, the National Comprehensive Cancer Network’s guidelines indicate MRI as optional in intermediate-risk prostate cancer evaluation. This project aims to elucidate whether MRI affects radiation treatment decisions for intermediate-risk prostate cancer. This was a retrospective study evaluating 210 patients with intermediate-risk prostate cancer, treated with definitive radiotherapy at our institution between 2019-2020. NCCN risk stratification criteria were used to define intermediate-risk prostate cancer. Patients were divided into two groups: those with pretreatment prostate MRI, and those without pretreatment prostate MRI. We compared the use of external beam radiotherapy, brachytherapy alone, brachytherapy boost, and androgen depravation therapy between the two groups. Inverse probability of treatment weighting was used to match the two groups for age, comorbidity index, American Urologic Association symptoms index, pretreatment PSA, grade group, and percent core involvement on prostate biopsy. Wilcoxon Rank Sum and Chi-squared tests were used to compare continuous and categorical variables. Of the patients who met the study’s eligibility criteria, 133 had a prostate MRI and 77 did not. Following propensity matching, there were no differences between baseline characteristics between the two groups. There were no statistically significant differences in treatments pursued between the two groups: 42% vs 47% were treated with brachytherapy alone, 40% vs 42% were treated with external beam radiotherapy alone, 18% vs 12% were treated with external beam radiotherapy with a brachytherapy boost, and 24% vs 17% received androgen deprivation therapy in the non-MRI and MRI groups, respectively. This analysis suggests that pretreatment MRI does not significantly impact radiation therapy or androgen deprivation therapy decisions in patients with intermediate-risk prostate cancer. Obtaining a pretreatment prostate MRI should be used judiciously and pursued only to answer a specific question, for which the answer is likely to impact treatment decision. Further follow up is needed to correlate MRI findings with their impacts on specific oncologic outcomes.

Keywords: magnetic resonance imaging, prostate cancer, definitive radiotherapy, gleason score 7

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Authors: Deniz Erçelen, Özlem Selcuk Bozkurt

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The course of daily human life calls for the need for memories and remembering the time and place for certain events. Recalling memories takes up a substantial amount of time for an individual. Unfortunately, scientists lack the proper technology to fully understand and observe different brain regions that interact to form or retrieve memories. The hippocampus, a complex brain structure located in the temporal lobe, plays a crucial role in memory. The hippocampus forms memories as well as allows the brain to retrieve them by ensuring that neurons fire together. This process is called “neural synchronization.” Sadly, the hippocampus is known to deteriorate often with age. Proteins and hormones, which repair and protect cells in the brain, typically decline as the age of an individual increase. With the deterioration of the hippocampus, an individual becomes more prone to memory loss. Many memory loss starts off as mild but may evolve into serious medical conditions such as dementia and Alzheimer’s disease. In their quest to fully comprehend how memories work, scientists have created many different kinds of technology that are used to examine the brain and neural pathways. For instance, Magnetic Resonance Imaging - or MRI- is used to collect detailed images of an individual's brain anatomy. In order to monitor and analyze brain functions, a different version of this machine called Functional Magnetic Resonance Imaging - or fMRI- is used. The fMRI is a neuroimaging procedure that is conducted when the target brain regions are active. It measures brain activity by detecting changes in blood flow associated with neural activity. Neurons need more oxygen when they are active. The fMRI measures the change in magnetization between blood which is oxygen-rich and oxygen-poor. This way, there is a detectable difference across brain regions, and scientists can monitor them. Electroencephalography - or EEG - is also a significant way to monitor the human brain. The EEG is more versatile and cost-efficient than an fMRI. An EEG measures electrical activity which has been generated by the numerous cortical layers of the brain. EEG allows scientists to be able to record brain processes that occur after external stimuli. EEGs have a very high temporal resolution. This quality makes it possible to measure synchronized neural activity and almost precisely track the contents of short-term memory. Science has come a long way in monitoring memories using these kinds of devices, which have resulted in the inspections of neurons and neural pathways becoming more intense and detailed.

Keywords: brain, EEG, fMRI, hippocampus, memories, neural pathways, neurons

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Authors: Selena Ferrian, Erin Mccaffrey, Toshie Saito, Aiqin Cao, Noah Greenwald, Mark Robert Nicolls, Trevor Bruce, Roham T. Zamanian, Patricia Del Rosario, Marlene Rabinovitch, Michael Angelo

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Recent experimental and clinical observations are advancing immunotherapies to clinical trials in pulmonary arterial hypertension (PAH). However, comprehensive mapping of the immune landscape in pulmonary arteries (PAs) is necessary to understand how immune cell subsets interact to induce pulmonary vascular pathology. We used multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to interrogate the immune landscape in PAs from idiopathic (IPAH) and hereditary (HPAH) PAH patients. Massive immune infiltration in I/HPAH was observed with intramural infiltration linked to PA occlusive changes. The spatial context of CD11c+DCs expressing SAMHD1, TIM-3 and IDO-1 within immune-enriched microenvironments and neutrophils were associated with greater immune activation in HPAH. Furthermore, CD11c-DC3s (mo-DC-like cells) within a smooth muscle cell (SMC) enriched microenvironment were linked to vessel score, proliferating SMCs, and inflamed endothelial cells. Experimental data in cultured cells reinforced a causal relationship between neutrophils and mo-DCs in mediating pulmonary arterial SMC proliferation. These findings merit consideration in developing effective immunotherapies for PAH.

Keywords: pulmonary arterial hypertension, vascular remodeling, indoleamine 2-3-dioxygenase 1 (IDO-1), neutrophils, monocyte-derived dendritic cells, BMPR2 mutation, interferon gamma (IFN-γ)

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Authors: Reza Behmanesh, Mohammad Nasrolahzadeh-Masouleh, Ehsan Khaksar, Saeed Bokaie

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Domestic rabbits (Oryctolagus cuniculus) are an excellent model for cardiovascular research because the size of these animals is more suitable for study and experimentation than smaller animals. One of the most important diagnostic imaging methods is echocardiography, which is used today to evaluate the anatomical and functional cardiovascular system and is one of the most accurate and sensitive non-invasive methods for examining heart disease. Ventricular function indices can be assessed with cardiac imaging techniques. One of these important cardiac parameters is the ejection fraction (EF), which has a valuable place along with other involved parameters. EF is a measure of the percentage of blood that comes out of the heart with each contraction. For this study, 100 adult and young standard domestic rabbits, six months to one year old and of both sexes (50 female and 50 male rabbits) without anesthesia and sedation were used. In this study, the mean EF in domestic rabbits studied in males was 58.753 ± 6.889 and in females, 61.397 ± 6.530, which are comparable to the items mentioned in the valid books and the average size of EF measured in this study; there is no significant difference between this research and other research. There was no significant difference in the percentage of EF between most weight groups, but there was a significant difference (p < 0.05) in weight groups (2161–2320 g and 2481–2640 g). Echocardiographic EF reference values for domestic rabbits (Oryctolagus cuniculus) non-anesthetized are presented, providing reference values for future studies.

Keywords: echocardiography, ejection fraction, rabbit, heart

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Authors: Walid Wahballah, Taher Bazan, Fawzy Eltohamy

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One of the important functions of the satellite attitude control system is to provide the required pointing accuracy and attitude stability for optical remote sensing satellites to achieve good image quality. Although offering noise reduction and increased sensitivity, time delay and integration (TDI) charge coupled devices (CCDs) utilized in high-resolution satellites (HRS) are prone to introduce large amounts of pixel smear due to the instability of the line of sight. During on-orbit imaging, as a result of the Earth’s rotation and the satellite platform instability, the moving direction of the TDI-CCD linear array and the imaging direction of the camera become different. The speed of the image moving on the image plane (focal plane) represents the image motion velocity whereas the angle between the two directions is known as the drift angle (β). The drift angle occurs due to the rotation of the earth around its axis during satellite imaging; affecting the geometric accuracy and, consequently, causing image quality degradation. Therefore, the image motion velocity vector and the drift angle are two important factors used in the assessment of the image quality of TDI-CCD based optical remote sensing satellites. A model for estimating the image motion velocity and the drift angle in HRS is derived. The six satellite attitude control parameters represented in the derived model are the (roll angle φ, pitch angle θ, yaw angle ψ, roll angular velocity φ֗, pitch angular velocity θ֗ and yaw angular velocity ψ֗ ). The influence of these attitude parameters on the image quality is analyzed by establishing a relationship between the image motion velocity vector, drift angle and the six satellite attitude parameters. The influence of the satellite attitude parameters on the image quality is assessed by the presented model in terms of modulation transfer function (MTF) in both cross- and along-track directions. Three different cases representing the effect of pointing accuracy (φ, θ, ψ) bias are considered using four different sets of pointing accuracy typical values, while the satellite attitude stability parameters are ideal. In the same manner, the influence of satellite attitude stability (φ֗, θ֗, ψ֗) on image quality is also analysed for ideal pointing accuracy parameters. The results reveal that cross-track image quality is influenced seriously by the yaw angle bias and the roll angular velocity bias, while along-track image quality is influenced only by the pitch angular velocity bias.

Keywords: high-resolution satellites, pointing accuracy, attitude stability, TDI-CCD, smear, MTF

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Authors: Murat Durucu

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Glaucoma is a condition of irreversible blindness, early diagnosis and appropriate interventions to make the patients able to see longer time. In this study, it addressed that the importance of developing a decision support system for glaucoma diagnosis. Glaucoma occurs when pressure happens around the eyes it causes some damage to the optic nerves and deterioration of vision. There are different levels ranging blindness of glaucoma disease. The diagnosis at an early stage allows a chance for therapies that slows the progression of the disease. In recent years, imaging technology from Heidelberg Retinal Tomography (HRT), Stereoscopic Disc Photo (SDP) and Optical Coherence Tomography (OCT) have been used for the diagnosis of glaucoma. This better accuracy and faster imaging techniques in response technique of OCT have become the most common method used by experts. Although OCT images or HRT precision and quickness, especially in the early stages, there are still difficulties and mistakes are occurred in diagnosis of glaucoma. It is difficult to obtain objective results on diagnosis and placement process of the doctor's. It seems very important to develop an objective decision support system for diagnosis and level the glaucoma disease for patients. By using OCT images and pattern recognition systems, it is possible to develop a support system for doctors to make their decisions on glaucoma. Thus, in this recent study, we develop an evaluation and support system to the usage of doctors. Pattern recognition system based computer software would help the doctors to make an objective evaluation for their patients. It is intended that after development and evaluation processes of the software, the system is planning to be serve for the usage of doctors in different hospitals.

Keywords: decision support system, glaucoma, image processing, pattern recognition

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: L. José, S. Vieira, E. Melo, A. R. Pinheiro

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Objectives: This study aims to characterize the stroke profile and the health care provided for people with a stroke in Luanda, Angola. Methods: A prospective longitudinal study was conducted at two Health centers, from March to November 2023, enrolling stroke patients. Data was gathered using a survey created by the researchers and validated by a health panel of experts from Angola. The analysis focused on demographic and stroke characteristics, as well as the care provided. Ethical approval and informed consent were obtained. Results: Preliminary results of a total of 186 patients are described, 122 from a Central Acute Care Hospital, with a mean age of 51.3±14.35 years old, a BMI of 26.7±4.15 kg/m2, 41% male, and 64 patients from a Rehabilitation Center, with 55.6±11.55 years old, a BMI of 27.0±3.8 kg/m2, 53% male. Ischemic stroke was reported as the most representative type in both centers (71.3% and 70.3%, respectively), though 100% of patients had no imaging diagnosis confirmation, neither data about the subtype was given. For patients admitted to the Hospital, discharge occurred before rehabilitation, and no follow-up was possible. No rehabilitation care was delivered in the first 7 days after the stroke. In the Rehabilitation Center, patient’s rehabilitation started in the late subacute phase, after a mean of 171.8±11.5 days. Conclusions: Stroke diagnosis lacks imaging confirmation, which is decisive for proper treatment, and rehabilitation starts during the late subacute phase, which is too late considering the international guidelines and the best window of opportunity for neuroplasticity and recovery. These results highlight the urgent need for the definition of Stroke-directed Health Care Policies in Angola.

Keywords: stroke, personalized health care, functional recovery, quality of life, health policies

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Authors: Julia Wimmers-Klick

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At the Canadian University of British Columbia's Faculty of Medicine, anatomy has traditionally been taught through a combination of lectures and dissection labs in the first two years, with radiology taught separately through lectures and online modules. However, this separation may leave students underprepared for medical practice, as medical imaging is essential for diagnosing anatomical and pathological conditions. To address this, a pilot project was initiated aimed at integrating radiological imaging into anatomy dissection labs from day one of medical school. The incorporated radiological images correlated with the current dissection areas. Additional stations were added within the lab, tailored to the specific content being covered. These stations focused on bones, and quiz questions, along with light-box exercises using radiographs, CT scans, and MRIs provided by the radiology department. The images used were free of pathologies. Examples of these will be presented in the poster. Feedback from short interviews with students and instructors has been positive, particularly among second-year students who appreciated the integration compared to their first-year experience. This low-budget approach was easy to implement but faced challenges, as lab instructors were not radiologists and occasionally struggled to answer students' questions. Instructors expressed a desire for basic training or a refresher course in radiology image reading, particularly focused on identifying healthy landmarks. Overall, all participants agreed that integrating radiology with anatomy reinforces learning during dissection, enhancing students' understanding and preparation for clinical practice.

Keywords: quality improvement, radiology education, anatomy education, integration

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Authors: Bruno RamaëL, GwenaëL Page, Catherine Knopf-Lenoir, Olivier Baledent, Anne-Virginie Salsac

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No routine technique currently exists for clinicians to measure the mechanical properties of vascular walls non-invasively. Most of the data available in the literature come from traction or dilatation tests conducted ex vivo on native blood vessels. The objective of the study is to develop a non-invasive characterization technique based on Magnetic Resonance Imaging (MRI) measurements of the deformation of vascular walls under pulsating blood flow conditions. The goal is to determine the mechanical properties of the vessels by inverse analysis, coupling imaging measurements and numerical simulations of the fluid-structure interactions. The hyperelastic properties are identified using Solidworks and Ansys workbench (ANSYS Inc.) solving an optimization technique. The vessel of interest targeted in the study is the common carotid artery. In vivo MRI measurements of the vessel anatomy and inlet velocity profiles was acquired along the facial vascular network on a cohort of 30 healthy volunteers: - The time-evolution of the blood vessel contours and, thus, of the cross-section surface area was measured by 3D imaging angiography sequences of phase-contrast MRI. - The blood flow velocity was measured using a 2D CINE MRI phase contrast (PC-MRI) method. Reference arterial pressure waveforms were simultaneously measured in the brachial artery using a sphygmomanometer. The three-dimensional (3D) geometry of the arterial network was reconstructed by first creating an STL file from the raw MRI data using the open source imaging software ITK-SNAP. The resulting geometry was then transformed with Solidworks into volumes that are compatible with Ansys softwares. Tetrahedral meshes of the wall and fluid domains were built using the ANSYS Meshing software, with a near-wall mesh refinement method in the case of the fluid domain to improve the accuracy of the fluid flow calculations. Ansys Structural was used for the numerical simulation of the vessel deformation and Ansys CFX for the simulation of the blood flow. The fluid structure interaction simulations showed that the systolic and diastolic blood pressures of the common carotid artery could be taken as reference pressures to identify the mechanical properties of the different arteries of the network. The coefficients of the hyperelastic law were identified using Ansys Design model for the common carotid. Under large deformations, a stiffness of 800 kPa is measured, which is of the same order of magnitude as the Young modulus of collagen fibers. Areas of maximum deformations were highlighted near bifurcations. This study is a first step towards patient-specific characterization of the mechanical properties of the facial vessels. The method is currently applied on patients suffering from facial vascular malformations and on patients scheduled for facial reconstruction. Information on the blood flow velocity as well as on the vessel anatomy and deformability will be key to improve surgical planning in the case of such vascular pathologies.

Keywords: identification, mechanical properties, arterial walls, MRI measurements, numerical simulations

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Mahdi Farajzadeh Ajirlou

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The detailed serious adverse effects raised the stresses around the safety of individuals who have gotten COVID-19 vaccines. Numerous verification referrers that disease with COV-19 causes neurological dysfunction in a significant proportion of influenced patients, where these side effects show up seriously amid the disease, and still less is known approximately the potential long-term results for the brain, where the loss of olfaction could be a neurological sign and simple indications of COVID-19. Since publishing effective clinical trial results of mRNA coronavirus disease 2019 (COVID-19) and injecting it to the volunteers in 2020, numerous reports have emerged approximately about cardiovascular complications followed by the mRNA vaccination. Vaccination-associated adenopathy could be a constant imaging finding after the organization of COVID-19 antibodies that will lead to a symptomatic problem in patients with shown or suspected cancer, in whom it may be vague from dangerous nodal inclusion. In spite of all the benefits and viability of the coronavirus infection 2019 (COVID-19) antibodies specified in later clinical trials, a few other post-vaccination side impacts, such as lymphadenopathy (LAP), were observed. Also, numerous variables, including financial conditions, have played a critical part in expanding the number of people with COVID-19 infection and also much more side effects in that country. Amid the Coronavirus widespread, Iran has been experiencing extreme sanctions, which has faced this nation with an extreme financial crisis. Additionally, with COVID-19 widespread, there was a developing concern around the abuse of imaging exams extraordinarily within the pediatric populace, which highlights the issues pointed out by this review.

Keywords: radiology, vaccines, COVID-19, side effect

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Authors: Cecilia Moreira, Rita Paiva, Daniela Macedo, Leonor Ribeiro, Isabel Fernandes, Luis Costa

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Background: Head and neck paragangliomas are a rare group of tumors with a large spectrum of clinical manifestations. The approach to evaluate and treat these lesions has evolved over the last years. Surgery was the standard for the approach of these patients, but nowadays new techniques of imaging and radiation therapy changed that paradigm. Despite advances in treating, the growth potential and clinical outcome of individual cases remain largely unpredictable. Objectives: Characterization of our institutional experience with clinical management of these tumors. Methods: This was a cross-sectional study of patients followed in our institution between 01 January and 31 December 2017 with paragangliomas of the head and neck and cranial base. Data on tumor location, catecholamine levels, and specific imaging modalities employed in diagnostic workup, treatment modality, tumor control and recurrence, complications of treatment and hereditary status were collected and summarized. Results: A total of four female patients were followed between 01 January and 31 December 2017 in our institution. The mean age of our cohort was 53 (± 16.1) years. The primary locations were at the level of the tympanic jug (n=2, 50%) and carotid body (n=2, 50%), and only one of the tumors of the carotid body presented pulmonary metastasis at the time of diagnosis. None of the lesions were catecholamine-secreting. Two patients underwent genetic testing, with no mutations identified. The initial clinical presentation was variable highlighting the decrease of visual acuity and headache as symptoms present in all patients. In one of the cases, loss of all teeth of the lower jaw was the presenting symptomatology. Observation with serial imaging, surgical extirpation, radiation, and stereotactic radiosurgery were employed as treatment approaches according to anatomical location and resectability of lesions. As post-therapeutic sequels the persistence of tinnitus and disabling pain stands out, presenting one of the patients neuralgia of the glossopharyngeal. Currently, all patients are under regular surveillance with a median follow up of 10 months. Conclusion: Ultimately, clinical management of these tumors remains challenging owing to heterogeneity in clinical presentation, the existence of multiple treatment alternatives, and potential to cause serious detriment to critical functions and consequently interference with the quality of life of the patients.

Keywords: clinical outcomes, head and neck, management, paragangliomas

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Authors: Zheng Yuxun

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This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

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Authors: Umedov Mekhroz, Griaznova Svetlana

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In connection with the growth of oncological diseases, the design of centers for diagnostics and the production of radiopharmaceuticals is the most relevant area of healthcare facilities. The design of new nuclear medicine centers should be carried out from the standpoint of solving the following tasks: the availability of medical care, functionality, environmental friendliness, sustainable development, improving the safety of drugs, the use of which requires special care, reducing the rate of environmental pollution, ensuring comfortable conditions for the internal microclimate, adaptability. The purpose of this article is to substantiate architectural and planning solutions, formulate recommendations and principles for the design of nuclear medicine centers and determine the connections between the production and medical functions of a building. The advantages of combining the production of radiopharmaceuticals and the department of medical care: less radiation activity is accumulated, the cost of the final product is lower, and there is no need to hire a transport company with a special license for transportation. A medical imaging department is a structural unit of a medical institution in which diagnostic procedures are carried out in order to gain an idea of the internal structure of various organs of the body for clinical analysis. Depending on the needs of a particular institution, the department may include various rooms that provide medical imaging using radiography, ultrasound diagnostics, and the phenomenon of nuclear magnetic resonance. The production of radiopharmaceuticals is an object intended for the production of a pharmaceutical substance containing a radionuclide and intended for introduction into the human body or laboratory animal for the purpose of diagnosis, evaluation of the effectiveness of treatment, or for biomedical research. The research methodology includes the following subjects: study and generalization of international experience in scientific research, literature, standards, teaching aids, and design materials on the topic of research; An integrated approach to the study of existing international experience of PET / CT scan centers and the production of radiopharmaceuticals; Elaboration of graphical analysis and diagrams based on the system analysis of the processed information; Identification of methods and principles of functional zoning of nuclear medicine centers. The result of the research is the identification of the design principles of nuclear medicine centers with the functions of the production of radiopharmaceuticals and the department of medical imaging. This research will be applied to the design and construction of healthcare facilities in the field of nuclear medicine.

Keywords: architectural planning solutions, functional zoning, nuclear medicine, PET/CT scan, production of radiopharmaceuticals, radiotherapy

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Authors: Cristina Maria Ribeiro Martins Pereira Caridade, Ana Rita Ferreira Morais

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The use of computational tools has become essential in the context of interactive learning, especially in engineering education. In the medical industry, teaching medical image processing techniques is a crucial part of training biomedical engineers, as it has integrated applications with healthcare facilities and hospitals. The aim of this article is to present a teaching-learning simulation tool developed in MATLAB using a graphical user interface for medical image fusion that explores different image fusion methodologies and processes in combination with image pre-processing techniques. The application uses different algorithms and medical fusion techniques in real time, allowing you to view original images and fusion images, compare processed and original images, adjust parameters, and save images. The tool proposed in an innovative teaching and learning environment consists of a dynamic and motivating teaching simulation for biomedical engineering students to acquire knowledge about medical image fusion techniques and necessary skills for the training of biomedical engineers. In conclusion, the developed simulation tool provides real-time visualization of the original and fusion images and the possibility to test, evaluate and progress the student’s knowledge about the fusion of medical images. It also facilitates the exploration of medical imaging applications, specifically image fusion, which is critical in the medical industry. Teachers and students can make adjustments and/or create new functions, making the simulation environment adaptable to new techniques and methodologies.

Keywords: image fusion, image processing, teaching-learning simulation tool, biomedical engineering education

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Authors: Yong Zhang

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Light has proven to be useful in a wide range of biomedical applications such as fluorescence imaging, photoacoustic imaging, optogenetics, photodynamic therapy, photothermal therapy, and light controlled drug/gene delivery. Taking photodynamic therapy (PDT) as an example, PDT has been proven clinically effective in early lung cancer, bladder cancer, head, and neck cancer and is the primary treatment for skin cancer as well. However, clinical use of PDT is severely constrained by the low penetration depth of visible light through thick tissue, limiting its use to target regions only a few millimeters deep. One way to enhance the range is to use invisible near-infrared (NIR) light within the optical window (700–1100nm) for biological tissues, extending the depth up to 1cm with no observable damage to the intervening tissue. We have demonstrated use of NIR-to-visible upconversion fluorescent nanoparticles (UCNPs), emitting visible fluorescence when excited by a NIR light at 980nm, as a nanotransducer for PDT to convert deep tissue-penetrating NIR light to visible light suitable for activating photosensitizers. The unique optical properties of UCNPs enable the upconversion wavelength to be tuned and matched to the activation absorption wavelength of the photosensitizer. At depths beyond 1cm, however, tissue remains inaccessible to light even within the NIR window, and this critical depth limitation renders existing phototherapy ineffective against most deep-seated cancers. We have demonstrated some new treatment modalities for deep-seated cancers based on UCNP hydrogel implants and miniaturized, wirelessly powered optoelectronic devices for light delivery to deep tissues.

Keywords: upconversion, fluorescent, nanoparticle, bioimaging, photodynamic therapy

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Authors: Chiung-Yun Chang, Po-Chou Chen, Jiun-Shiang Tzeng, Ka-Wai Mac, Chia-Chi Hsiao, Jo-Chi Jao

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This study aimed to measure R2* relaxation rates in the liver of New Zealand White (NZW) rabbits. R2* relaxation rate has been widely used in various hepatic diseases for iron overload by quantifying iron contents in liver. R2* relaxation rate is defined as the reciprocal of T2* relaxation time and mainly depends on the composition of tissue. Different tissues would have different R2* relaxation rates. The signal intensity decay in Magnetic resonance imaging (MRI) may be characterized by R2* relaxation rates. In this study, a 1.5T GE Signa HDxt whole body MR scanner equipped with an 8-channel high resolution knee coil was used to observe R2* values in NZW rabbit’s liver and muscle. Eight healthy NZW rabbits weighted 2 ~ 2.5 kg were recruited. After anesthesia using Zoletil 50 and Rompun 2% mixture, the abdomen of rabbit was landmarked at the center of knee coil to perform 3-plane localizer scan using fast spoiled gradient echo (FSPGR) pulse sequence. Afterward, multi-planar fast gradient echo (MFGR) scans were performed with 8 various echo times (TEs) (2/4/6/8/10/12/14/16 ms) to acquire images for R2* calculations. Regions of interest (ROIs) at liver and muscle were measured using Advantage workstation. Finally, the R2* was obtained by a linear regression of ln(SI) on TE. The results showed that the longer the echo time, the smaller the signal intensity. The R2* values of liver and muscle were 44.8  10.9 s-1 and 37.4  9.5 s-1, respectively. It implies that the iron concentration of liver is higher than that of muscle. In conclusion, R2* is correlated with iron contents in tissue. The correlations between R2* and iron content in NZW rabbit might be valuable for further exploration.

Keywords: liver, magnetic resonance imaging, muscle, R2* relaxation rate

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Awad Mohamed Elkhadir, Rajab M. Ben Yousef

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Background/Aim: Radiological technologists are medical professionals who perform diagnostic imaging tests such as X-rays, magnetic resonance imaging (MRI) scans, and computer tomography (CT) scans. Despite the recognition of image interpretation by British radiologists, it is still considered a problem in the Arab world. This study evaluates the perceptions of radiologists in the Middle East concerning the plain image interpretation of adults by radiologic technologist specialists. Methods: This is a cross-sectional study that follows a quantitative approach. A close-ended questionnaire was distributed among 103 participants who were radiologists by profession from various hospitals in Saudi Arabia and Sudan. The gathered data was then analyzed through Statistical Package for Social Sciences (SPSS). Results: The results showed that 29% recognized the Radiologic Technologist Specialist (RTS) role of writing image reports, while 61% did not. A total of 38% of participants believed that RTS image interpretation would help diagnose unreported radiographs. 47% of the sample responded that the workload and stress on radiologists would reduce by allowing reporting for RTS, while 37% did not. Lastly, 43% believe that image interpretation by RTS can be introduced into the Middle East in the future. Conclusion: The study's findings reveal that the combination of image reporting and radiography improves the care of the patients. The study's outcomes also show that the burden of the medical practitioners reduces due to image reporting of the radiographers. Further researches need to be conducted in the Arab World to obtain and measure the associated factors of the desired criteria.

Keywords: Arab world, image interpretation, radiographer, radiologist, Saudi Arabia, Sudan

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Authors: Daud Muhammad

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Introduction: Ankle radiographs are frequently requested in Emergency Departments (ED) for patients presenting with traumatic ankle pain. The Ottawa Ankle Rules (OAR) serve as a clinical guideline to determine the necessity of these radiographs, aiming to reduce unnecessary imaging. This audit was conducted to evaluate the adequacy of clinical information provided in radiograph requests in relation to the OAR. Methods: A retrospective analysis was performed on 50 consecutive ankle radiograph requests under ED clinicians' names for patients aged above 5 years, specifically excluding follow-up radiographs for known fractures. The study assessed whether the provided clinical information met the criteria outlined by the OAR. Results: The audit revealed that none of the 50 radiograph requests contained sufficient information to satisfy the Ottawa Ankle Rules. Furthermore, 10 out of the 50 radiographs (20%) identified fractures. Discussion: The findings indicate a significant lack of adherence to the OAR, suggesting potential overuse of radiography and unnecessary patient exposure to radiation. This non-compliance may also contribute to increased healthcare costs and resource utilization, as well as possible delays in diagnosis and treatment. Recommendations: To address these issues, the following recommendations are proposed: (1) Education and Training: Enhance awareness and training among ED clinicians regarding the OAR. (2) Standardised Request Forms: Implement changes to imaging request forms to mandate relevant information according to the OAR. (3) Scan Vetting: Promote awareness among radiographers to discuss the appropriateness of scan requests with clinicians. (4) Regular re-audits should be conducted to monitor improvements in compliance.

Keywords: Ottawa ankle rules, ankle radiographs, emergency department, traumatic pain

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Authors: Adenike O. Olatunji-Akioye, Emmanual B Farayola

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In order to improve the animal protein recommended daily intake of Nigerians, there is an upsurge in breeding of hitherto shunned food animals one of which is the rabbit. Radiography and ultrasonography are tools for diagnosing disease and evaluating the anatomical architecture of parts of the body non-invasively. As the rabbit is becoming a more important food animal, to achieve improved breeding of these animals, the best of the species form a breeding stock and will usually depend on breeding soundness which may be evaluated by assessment of the male reproductive organs by these tools. Four male intact rabbits weighing between 1.2 to 1.5 kg were acquired and acclimatized for 2 weeks. Dorsoventral views of the testes were acquired using a digital radiographic machine and a 5 MHz portable ultrasound scanner was used to acquire images of the testes in longitudinal, sagittal and transverse planes. Radiographic images acquired revealed soft tissue images of the testes in all rabbits. The testes lie in individual scrotal sacs sides on both sides of the midline at the level of the caudal vertebrae and thus are superimposed by caudal vertebrae and the caudal limits of the pelvic girdle. The ultrasonographic images revealed mostly homogenously hypoechogenic testes and a hyperechogenic mediastinum testis. The dorsal and ventral poles of the testes were heterogeneously hypoechogenic and correspond to the epididymis and spermatic cord. The rabbit is unique in the ability to retract the testes particularly when stressed and so careful and stressless handling during the procedures is of paramount importance. The imaging of rabbit testes can be safely done using both imaging methods but ultrasonography is a better method of assessment and evaluation of soundness for breeding.

Keywords: breeding soundness, rabbit, radiography, ultrasonography

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Authors: K. Hinde, R. Bookun, P. Tran

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Percutaneous CT guided biopsies provide a fast, minimally invasive, cost effective and safe method for obtaining tissue for histopathology and culture. Standards for diagnostic yield vary depending on whether the tissue is being obtained for histopathology or culture. We present a retrospective audit from Western Health in Melbourne Australia over a 12-month period which aimed to determine the diagnostic yield, technical success and complication rate for CT guided bone biopsies and identify factors affecting these results. The digital imaging storage program (Synapse Picture Archiving and Communication System – Fujifilm Australia) was analysed with key word searches from October 2015 to October 2016. Nineteen CT guided bone biopsies were performed during this time. The most common referring unit was oncology, work up imaging included CT, MRI, bone scan and PET scan. The complication rate was 0%, overall diagnostic yield was 74% with a technical success of 95%. When performing biopsies for histologic analysis diagnostic yield was 85% and when performing biopsies for bacterial culture diagnostic yield was 60%. There was no significant relationship identified between size of lesion, distance of lesion to skin, lesion appearance on CT, the number of samples taken or gauge of needle to diagnostic yield or technical success. CT guided bone biopsy at Western Health meets the standard reported at other major clinical centres for technical success and safety. It is a useful investigation in identification of primary malignancy in distal bone metastases.

Keywords: bone biopsy, computed tomography, core biopsy, histopathology

Procedia PDF Downloads 199

Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

Procedia PDF Downloads 105