Search results for: time-lapse imaging data

Authors: Ramandeep Kaur, Gurjit Singh Bhathal

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Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.

Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations

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Authors: H. Yousefnia, S. Zolghadri, S. Shanesazzadeh, A.Lahooti, A. R. Jalilian

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In this study, 68Ga-ECC and 67Ga-ECC were both prepared with the radiochemical purity of higher than 97% in less than 30 min. The biodistribution data for 68Ga-ECC showed the extraction of the most of the activity from the urinary tract. The absorbed dose was estimated based on biodistribution data in mice by the medical internal radiation dose (MIRD) method. Comparison between human absorbed dose estimation for these two agents indicated the values of approximately ten-fold higher after injection of 67Ga-ECC than 68Ga-ECC in the most organs. The results showed that 68Ga-ECC can be considered as a more potential agent for renal imaging compared to 67Ga-ECC.

Keywords: effective absorbed dose, ethylenecysteamine cysteine, Ga-67, Ga-68

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Authors: Ali Al Orf, Khawaja Bilal Waheed

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Background and objective: Joubert syndrome (JS) is a rare, autosomal-recessive condition. Early recognition is important for management and counseling. Magnetic resonance imaging (MRI) can help in diagnosis. Therefore, we sought to evaluate clinical presentation and MRI findings in Joubert syndrome and related disorders. Method: A retrospective review of genetically proven cases of Joubert syndromes and related disorders was reviewed for their clinical presentation, demographic information, and magnetic resonance imaging findings in a period of the last 10 years. Two radiologists documented magnetic resonance imaging (MRI) findings. The presence of hypoplasia of the cerebellar vermis with hypoplasia of the superior cerebellar peduncle resembling the “Molar Tooth Sign” in the mid-brain was documented. Genetic testing results were collected to label genes linked to the diagnoses. Results: Out of 12 genetically proven JS cases, most were females (9/12), and nearly all presented with hypotonia, ataxia, developmental delay, intellectual impairment, and speech disorders. 5/12 children presented at age of 1 or below. The molar tooth sign was seen in 10/12 cases. Two cases were associated with other brain findings. Most of the cases were found associated with consanguineous marriage Conclusion and discussion: The molar tooth sign is a frequent and reliable sign of JS and related disorders. Genes related to defective cilia result in malfunctioning in the retina, renal tubule, and neural cell migration, thus producing heterogeneous syndrome complexes known as “ciliopathies.” Other ciliopathies like Senior-Loken syndrome, Bardet Biedl syndrome, and isolated nephronophthisis must be considered as the differential diagnosis of JS. The main imaging findings are the partial or complete absence of the cerebellar vermis, hypoplastic cerebellar peduncles (giving MTS), and (bat-wing appearance) fourth ventricular deformity. LimitationsSingle-center, small sample size, and retrospective nature of the study were a few of the study limitations.

Keywords: Joubart syndrome, magnetic resonance imaging, molar tooth sign, hypotonia

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Authors: Mohmmad A. Obeidat, Amjed Al Fahoum, Ayman M. Mansour

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The recognition of an abnormal activity of the brain functionality is a vital issue. To determine the type of the abnormal activity either a brain image or brain signal are usually considered. Imaging localizes the defect within the brain area and relates this area with somebody functionalities. However, some functions may be disturbed without affecting the brain as in epilepsy. In this case, imaging may not provide the symptoms of the problem. A cheaper yet efficient approach that can be utilized to detect abnormal activity is the measurement and analysis of the electroencephalogram (EEG) signals. The main goal of this work is to come up with a new method to facilitate the classification of the abnormal and disorder activities within the brain directly using EEG signal processing, which makes it possible to be applied in an on-line monitoring system.

Keywords: EEG, wavelet, epilepsy, detection

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Authors: Matej Patzelt, Jana Mrzilkova, Jan Dudak, Frantisek Krejci, Jan Zemlicka, Zdenek Wurst, Petr Zach, Vladimir Musil

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Introduction: Micro-CT is well used for examination of bone structures and teeth. On the other hand visualization of the soft tissues is still limited. The goal of our study was to elaborate methodology for soft tissue samples imaging in micro-CT. Methodology: We used organs of rats and mice. We either did a preparation of the organs and fixation in contrast solution or we did cannulation of blood vessels and their injection for imaging of the vascular system. First, we scanned native specimens, then we created corrosive specimens by resins. In the next step, we injected vascular system either by Aurovist contrast agent or by Exitron. In the next step, we focused on soft tissues contrast increase. We scanned samples fixated in Lugol solution, samples fixated in pure ethanol and in formaldehyde solution. All used methods were afterwards compared. Results: Native specimens did not provide sufficient contrast of the tissues in any of organs. Corrosive samples of the blood stream provided great contrast and details; on the other hand, it was necessary to destroy the organ. Further examined possibility was injection of the AuroVist contrast that leads to the great bloodstream contrast. Injection of Exitron contrast agent comparing to Aurovist did not provide such a great contrast. The soft tissues (kidney, heart, lungs, brain, and liver) were best visualized after fixation in ethanol. This type of fixation showed best results in all studied tissues. Lugol solution had great results in muscle tissue. Fixation by formaldehyde solution showed similar quality of contrast in the tissues like ethanol. Conclusion: Before imaging, we need to, first, determinate which structures of the soft tissues we want to visualize. In the case of the bloodstream, the best was AuroVist and corrosive specimens. Muscle tissue is best visualized by Lugol solution. In the case of the organs containing cavities, like kidneys or brain, the best way was ethanol fixation.

Keywords: experimental imaging, fixation, micro-CT, soft tissues

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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: Sergio Tovar-Pérez, Sebastian Töpfer, Markus Gräfe

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The work proposes a technique that decreases the detection acquisition time of quantum holography schemes down to one-third; this allows the possibility to image moving objects. Since its invention, quantum holography with undetected photon schemes has gained interest in the scientific community. This is mainly due to its ability to tailor the detected wavelengths according to the needs of the scheme implementation. Yet this wavelength flexibility grants the scheme a wide range of possible applications; an important matter was yet to be addressed. Since the scheme uses digital phase-shifting techniques to retrieve the information of the object out of the interference pattern, it is necessary to acquire a set of at least four images of the interference pattern along with well-defined phase steps to recover the full object information. Hence, the imaging method requires larger acquisition times to produce well-resolved images. As a consequence, the measurement of moving objects remains out of the reach of the imaging scheme. This work presents the use and implementation of a spatial light modulator along with a digital holographic technique called quasi-parallel phase-shifting. This technique uses the spatial light modulator to build a structured phase image consisting of a chessboard pattern containing the different phase steps for digitally calculating the object information. Depending on the reduction in the number of needed frames, the acquisition time reduces by a significant factor. This technique opens the door to the implementation of the scheme for moving objects. In particular, the application of this scheme in imaging alive specimens comes one step closer.

Keywords: quasi-parallel phase shifting, quantum imaging, quantum holography, quantum metrology

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Authors: Van Tran Thi Thuy, Dukjoon Kim

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A series of pH- and thermosensitive poly(N-isopropyl acrylamide-co-acrylic acid) were synthesized by radical polymerization and grafted on poly succinimide backbones. The poly succinimide derivatives synthesized were coated on iron oxide magnetic nanoparticles for potential applications in drug delivery systems with theranostic and molecular imaging. The structure of polymer shell was confirmed by FT-IR, H-NMR spectroscopies. Its thermal behavior was tested by UV-Vis spectroscopy. The particle size and its distribution are measured by dynamic light scattering (DLS) and transmission electron microscope (TEM). The mean diameter of the core-shell structure is from 20 to 80 nm.

Keywords: magnetic, nano, PNIPAM, polysuccinimide

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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: Yunhe Chen, Xinyun Liu, Qian Wang, Jianan Li

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Background Cochlear implants (CIs) are currently the primary effective treatment for severe or profound sensorineural hearing loss. As China's population ages and the number of young children rises, the demand for MRI for CI patients is expected to increase. Methods Reviewed MRI cases of 25 CI patients between 2015 and 2024, assessed imaging auditory outcomes and adverse reactions. Use the adverse event record sheet and accompanying medication sheet to record follow-up measures. Results Most CI patients undergoing MRI may face risks such as artifacts, pain, redness, swelling, tissue damage, bleeding, and magnet displacement or demagnetization. Twenty-five CI patients in our hospital were reviewed. Seven patient underwent 3.0 T MR, the others underwent 1.5 T MR. The manufacturers are 18 cases in Austria, 5 cases in Australia and 2 cases in Nurotron. Among them, one patient with bilateral CI underwent 1.5 T MR examination after head pressure bandaging, and the left magnet was displaced (CI24RE Series, Australia). This patient underwent surgical replacement of the magnet under general anesthesia. Six days after the operation, the patient's feedback indicated that the performance of the cochlear implant was consistent with the previous results following the reactivation of the external device. Based on the experience of our hospital, we proposed the feasible management scheme of MRI examination procedure for CI patients. This plan should include a module for confirming MRI imaging parameters, informed consent, educational materials for patients, and other safety measures to ensure that patients receive imaging results safely and effectively, implify clinical. Conclusion As indications for both MRI and cochlear implantation expand，the number of MRI studies recommended for patients with cochlear implants will also increase. The process and management scheme proposed in this study can help to obtain imaging results safely and effectively, and reduce clinical stress.

Keywords: cochlear implantation, MRI, magnet, displacement

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Authors: Ashwani Kumar Aggarwal

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NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: H. Feza Carlak, N. G. Gencer

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To increase the temperature contrast in thermal images, the characteristics of the electrical conductivity and thermal imaging modalities can be combined. In this experimental study, it is objected to observe whether the temperature contrast created by the tumor tissue can be improved just due to the current application within medical safety limits. Various thermal breast phantoms are developed to simulate the female breast tissue. In vitro experiments are implemented using a thermal infrared camera in a controlled manner. Since experiments are implemented in vitro, there is no metabolic heat generation and blood perfusion. Only the effects and results of the electrical stimulation are investigated. Experimental study is implemented with two-dimensional models. Temperature contrasts due to the tumor tissues are obtained. Cancerous tissue is determined using the difference and ratio of healthy and tumor images. 1 cm diameter single tumor tissue causes almost 40 °mC temperature contrast on the thermal-breast phantom. Electrode artifacts are reduced by taking the difference and ratio of background (healthy) and tumor images. Ratio of healthy and tumor images show that temperature contrast is increased by the current application.

Keywords: medical diagnostic imaging, breast phantom, active thermography, breast cancer detection

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Authors: Chih Jou Hsiao, Chung Ming Lo, Li Chun Hsieh

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Brain tumor is not the cancer having high incidence rate, but its high mortality rate and poor prognosis still make it as a big concern. On clinical examination, the grading of brain tumors depends on pathological features. However, there are some weak points of histopathological analysis which can cause misgrading. For example, the interpretations can be various without a well-known definition. Furthermore, the heterogeneity of malignant tumors is a challenge to extract meaningful tissues under surgical biopsy. With the development of magnetic resonance imaging (MRI), tumor grading can be accomplished by a noninvasive procedure. To improve the diagnostic accuracy further, this study proposed a computer-aided diagnosis (CAD) system based on MRI features to provide suggestions of tumor grading. Gliomas are the most common type of malignant brain tumors (about 70%). This study collected 34 glioblastomas (GBMs) and 73 lower-grade gliomas (LGGs) from The Cancer Imaging Archive. After defining the region-of-interests in MRI images, multiple quantitative morphological features such as region perimeter, region area, compactness, the mean and standard deviation of the normalized radial length, and moment features were extracted from the tumors for classification. As results, two of five morphological features and three of four image moment features achieved p values of <0.001, and the remaining moment feature had p value <0.05. Performance of the CAD system using the combination of all features achieved the accuracy of 83.18% in classifying the gliomas into LGG and GBM. The sensitivity is 70.59% and the specificity is 89.04%. The proposed system can become a second viewer on clinical examinations for radiologists.

Keywords: brain tumor, computer-aided diagnosis, gliomas, magnetic resonance imaging

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Authors: Thieu-Thi Tra My

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Undifferentiated embryonal sarcoma of the liver (UESL), a rare malignant mesenchymal tumor, is commonly seen in children. The symptoms and imaging were not specific, so it could be mimicked with other tumors or liver abscesses. The tumor often appears as a large heterogeneous echoic solid mass with small cystic areas while showing a cyst-like appearance on CT and MRI. The histopathological manifestation of the UESL consisted of stellate-shaped and spindle cells scattered on a myxoid background with high mitotic count. Cells with multiple or bizarre nuclear were also observed. Here, we aimed to describe a 9-year-old male diagnosed with UESL focused on imaging and histopathological characteristics.

Keywords: undifferentiated embryonal sarcoma of liver, UESL, liver sarcoma, liver tumor, children

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Authors: Sonal Sethi, Mukesh Yadav, Abhimanyu Gupta

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The upcoming field of radiogenomics has the potential to upgrade the role of imaging in lung cancer management by noninvasive characterization of tumor histology and genetic microenvironment. Receptor positivity like epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) genotyping are critical in lung adenocarcinoma for treatment. As conventional identification of receptor positivity is an invasive procedure, we analyzed the features on non-invasive computed tomography (CT), which predicts the receptor positivity in lung adenocarcinoma. Retrospectively, we did a comprehensive study from 77 proven lung adenocarcinoma patients with CT images, EGFR and ALK receptor genotyping, and clinical information. Total 22/77 patients were receptor-positive (15 had only EGFR mutation, 6 had ALK mutation, and 1 had both EGFR and ALK mutation). Various morphological characteristics and metastatic distribution on CT were analyzed along with the clinical information. Univariate and multivariable logistic regression analyses were used. On multivariable logistic regression analysis, we found spiculated margin, lymphangitic spread, air bronchogram, pleural effusion, and distant metastasis had a significant predictive value for receptor mutation status. On univariate analysis, air bronchogram and pleural effusion had significant individual predictive value. Conclusions: Receptor positive lung cancer has characteristic imaging features compared with nonreceptor positive lung adenocarcinoma. Since CT is routinely used in lung cancer diagnosis, we can predict the receptor positivity by a noninvasive technique and would follow a more aggressive algorithm for evaluation of distant metastases as well as for the treatment.

Keywords: lung cancer, multidisciplinary cancer care, oncologic imaging, radiobiology

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Ashraf Abuelhaija, Klaus Solbach

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In Ultra high-field MRI scanners (3T and higher), parallel RF transmission techniques using multiple RF chains with multiple transmit elements are a promising approach to overcome the high-field MRI challenges in terms of inhomogeneity in the RF magnetic field and SAR. However, mutual coupling between the transmit array elements disturbs the desirable independent control of the RF waveforms for each element. This contribution demonstrates a 18 dB improvement of decoupling (isolation) performance due to the very low output impedance of our 1 kW power amplifier.

Keywords: EM coupling, inter-element isolation, magnetic resonance imaging (mri), parallel transmit

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Authors: Muhammad Hassan Khalil, Xu Jiadong

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Early detection through screening is the best tool short of a perfect treatment against the malignant tumor inside the breast of a woman. By detecting cancer in its early stages, it can be recognized and treated before it has the opportunity to spread and change into potentially dangerous. Microwave tomography is a new imaging method based on contrast in dielectric properties of materials. The mathematical theory of microwave tomography involves solving an inverse problem for Maxwell’s equations. In this paper, we present designed antenna for breast cancer detection, which will use in microwave tomography configuration.

Keywords: microwave imaging, inverse scattering, breast cancer, malignant tumor detection

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Authors: Grange Sylvain, Plancher Ronan, Reurink Guustav, Croisille Pierre, Edouard Pascal

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The primary objective of this study was to analyze the potential correlation between the pain experienced at the time of a hamstring muscle injury and the volume of the lesion measured on MRI. The secondary objectives were to analyze a correlation between this pain and the lesion grade as well as the affected hamstring muscle. We performed a retrospective analysis of the data collected in a prospective, multicenter, non-interventional cohort study (HAMMER). Patients with suspected hamstring muscle injury had an MRI after the injury and at the same time were evaluated for their pain intensity experienced at the time of the injury with a Numerical Pain Rating Scale (NPRS) from 0 to 10. A total of 61 patients were included in the present analysis. MRIs were performed in an average of less than 8 days. There was a significant correlation between pain and the injury volume (r=0.287; p=0.025). There was no significant correlation between the pain and the lesion grade (p>0.05), nor between the pain and affected hamstring muscle (p>0.05). Pain at the time of injury appeared to be correlated with the volume of muscle affected. These results confirm the value of a clinical approach in the initial evaluation of hamstring injuries to better select patients eligible for further imaging.

Keywords: hamstring muscle injury, MRI, volume lesion, pain

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Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

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Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

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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: Nizar Karim Uribe-Orihuela, Fernando Brambila-Paz, Ivette Caldelas, Rodrigo Montufar-Chaveznava

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In this paper, we present the advances corresponding to the implementation of a strategy to visualize geographical data using a Software Development Kit (SDK) for video games. We use multispectral images from Landsat 7 platform and Laser Imaging Detection and Ranging (LIDAR) data from The National Institute of Geography and Statistics of Mexican (INEGI). We select a place of interest to visualize from Landsat platform and make some processing to the image (rotations, atmospheric correction and enhancement). The resulting image will be our gray scale color-map to fusion with the LIDAR data, which was selected using the same coordinates than in Landsat. The LIDAR data is translated to 8-bit raw data. Both images are fused in a software developed using Unity (an SDK employed for video games). The resulting image is then displayed and can be explored moving around. The idea is the software could be used for students of geology and geophysics at the Engineering School of the National University of Mexico. They will download the software and images corresponding to a geological place of interest to a smartphone and could virtually visit and explore the site with a virtual reality visor such as Google cardboard.

Keywords: virtual reality, interactive technologies, geographical data visualization, video games technologies, educational material

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Authors: Aziz Ikhlef

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Most of multi-slices CT scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80kVp and 140kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Chao Wang, Zuxue Xia, Wenhai Xia, Rui Wang, Jiayuan Hu, Rui Cheng

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Aiming at the application of indoor personnel positioning under smog conditions, this paper proposes a 3D positioning method based on the IWR1443 millimeter wave radar sensor. The problem that millimeter-wave radar cannot effectively form contours in 3D point cloud imaging is solved. The results show that the method can effectively achieve indoor positioning and scene construction, and the maximum positioning error of the system is 0.130m.

Keywords: indoor positioning, millimeter wave radar, IWR1443 sensor, point cloud imaging

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Authors: Leila Keshavarz Afshar, Hedieh Sajedi

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Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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Authors: Christian Röling, Elena Y. Poimanova, Vladimir V. Bruevich

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Here we demonstrate a non-destructive optical technique to localize and characterize single crystals of semiconductive organic materials – Spectroscopic Imaging Ellipsometry. With a combination of microscopy and ellipsometry, it is possible to characterize even micro-sized thin film crystals on plane surface regarding anisotropy, optical properties, crystalline domains and thickness. The semiconducting thiophene-phenylene co-oligomer 1,4-bis(5'-hexyl-[2,2'-bithiophen]-5-yl)benzene (dHex-TTPTT) crystals were grown by solvent based self-assembly technique on silicon substrate with 300 nm thermally silicon dioxide. The ellipsometric measurements were performed with an Ep4-SE (Accurion). In an ellipsometric high-contrast image of the complete sample, we have localized high-quality single crystals. After demonstrating the uniaxial anisotropy of the crystal by using Müller-Matrix imaging ellipsometry, we determined the optical axes by rotating the sample and performed spectroscopic measurements (λ = 400-700 nm) in 5 nm intervals. The optical properties were described by using a Lorentz term in the Ep4-Model. After determining the dispersion of the crystals, we converted a recorded Delta and Psi-map into a 2D thickness image. Based on a quantitative analysis of the resulting thickness map, we have calculated the height of a molecular layer (3.49 nm).

Keywords: anisotropy, ellipsometry, SCFET, thin film

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Authors: Gus Calderon, Richard McCreight, Tammy Schwartz

Abstract:

Forensic analysis of community wildfire destruction in California has shown that reducing or removing flammable vegetation in proximity to buildings and structures is one of the most important wildfire defenses available to homeowners. State laws specify the requirements for homeowners to create and maintain defensible space around all structures. Unfortunately, this decades-long effort had limited success due to noncompliance and minimal enforcement. As a result, vulnerable communities continue to experience escalating human and economic costs along the wildland-urban interface (WUI). Quantifying vegetative fuels at both the community and parcel scale requires detailed imaging from an aircraft with remote sensing technology to reduce uncertainty. FireWatch has been delivering high spatial resolution (5” ground sample distance) wildfire hazard maps annually to the community of Rancho Santa Fe, CA, since 2019. FireWatch uses a multispectral imaging system mounted onboard an aircraft to create georeferenced orthomosaics and spectral vegetation index maps. Using proprietary algorithms, the vegetation type, condition, and proximity to structures are determined for 1,851 properties in the community. Secondary data processing combines object-based classification of vegetative fuels, assisted by machine learning, to prioritize mitigation strategies within the community. The remote sensing data for the 10 sq. mi. community is divided into parcels and sent to all homeowners in the form of defensible space maps and reports. Follow-up aerial surveys are performed annually using repeat station imaging of fixed GPS locations to address changes in defensible space, vegetation fuel cover, and condition over time. These maps and reports have increased wildfire awareness and mitigation efforts from 40% to over 85% among homeowners in Rancho Santa Fe. To assist homeowners fighting increasing insurance premiums and non-renewals, FireWatch has partnered with Black Swan Analytics, LLC, to leverage the multispectral imagery and increase homeowners’ understanding of wildfire risk drivers. For this study, a subsample of 100 parcels was selected to gain a comprehensive understanding of wildfire risk and the elements which can be mitigated. Geospatial data from FireWatch’s defensible space maps was combined with Black Swan’s patented approach using 39 other risk characteristics into a 4score Report. The 4score Report helps property owners understand risk sources and potential mitigation opportunities by assessing four categories of risk: Fuel sources, ignition sources, susceptibility to loss, and hazards to fire protection efforts (FISH). This study has shown that susceptibility to loss is the category residents and property owners must focus their efforts. The 4score Report also provides a tool to measure the impact of homeowner actions on risk levels over time. Resiliency is the only solution to breaking the cycle of community wildfire destruction and it starts with high-quality data and education.

Keywords: defensible space, geospatial data, multispectral imaging, Rancho Santa Fe, susceptibility to loss, wildfire risk.

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Authors: Maha Al-Soudani, Gilles Klysz, Jean-Paul Balayssac

Abstract:

The aim of this paper is to use Ground Penetrating Radar (GPR) as a non-destructive testing (NDT) method to increase its accuracy in recognizing the geometric reinforced concrete structures and in particular, the position of steel bars. This definition will help the managers to assess the state of their structures on the one hand vis-a-vis security constraints and secondly to quantify the need for maintenance and repair. Several configurations of acquisition and processing of the simulated signal were tested to propose and develop an appropriate imaging algorithm in the propagation medium to locate accurately the rebar. A subsequent experimental validation was used by testing the imaging algorithm on real reinforced concrete structures. The results indicate that, this algorithm is capable of estimating the reinforcing steel bar position to within (0-1) mm.

Keywords: GPR, NDT, Reinforced concrete structures, Rebar location.

Procedia PDF Downloads 502

Authors: Kristina Sakalauskiene, Renaldas Raisutis, Gintare Linkeviciute, Skaidra Valiukeviciene

Abstract:

Cutaneous melanoma is a melanocytic skin tumour, which has a very poor prognosis while is highly resistant to treatment and tends to metastasize. Thickness of melanoma is one of the most important biomarker for stage of disease, prognosis and surgery planning. In this study, we hypothesized that the automatic analysis of spectrophotometric images and high-frequency ultrasonic 2D data can improve differential diagnosis of cutaneous melanoma and provide additional information about tumour penetration depth. This paper presents the novel complex automatic system for non-invasive melanocytic skin tumour differential diagnosis and penetration depth evaluation. The system is composed of region of interest segmentation in spectrophotometric images and high-frequency ultrasound data, quantitative parameter evaluation, informative feature extraction and classification with linear regression classifier. The segmentation of melanocytic skin tumour region in ultrasound image is based on parametric integrated backscattering coefficient calculation. The segmentation of optical image is based on Otsu thresholding. In total 29 quantitative tissue characterization parameters were evaluated by using ultrasound data (11 acoustical, 4 shape and 15 textural parameters) and 55 quantitative features of dermatoscopic and spectrophotometric images (using total melanin, dermal melanin, blood and collagen SIAgraphs acquired using spectrophotometric imaging device SIAscope). In total 102 melanocytic skin lesions (including 43 cutaneous melanomas) were examined by using SIAscope and ultrasound system with 22 MHz center frequency single element transducer. The diagnosis and Breslow thickness (pT) of each MST were evaluated during routine histological examination after excision and used as a reference. The results of this study have shown that automatic analysis of spectrophotometric and high frequency ultrasound data can improve non-invasive classification accuracy of early-stage cutaneous melanoma and provide supplementary information about tumour penetration depth.

Keywords: cutaneous melanoma, differential diagnosis, high-frequency ultrasound, melanocytic skin tumours, spectrophotometric imaging

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Authors: O. J. G. Somsen

Abstract:

One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simpler spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various width we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application

Keywords: anomaly detection, spectroscopic line imaging, image analysis, outdoor detection

Procedia PDF Downloads 479