Search results for: medical imaging

Authors: A. Abbas, X. Tridon, J. Michelon

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In the electronic or in the photovoltaic industries, components are made from wafers which are stacks of thin film layers of a few nanometers to serval micrometers thickness. Early evaluation of the bounding quality between different layers of a wafer is one of the challenges of these industries to avoid dysfunction of their final products. Traditional pump-probe experiments, which have been developed in the 70’s, give a partial solution to this problematic but with a non-negligible drawback. In fact, on one hand, these setups can generate and detect ultra-high ultrasounds frequencies which can be used to evaluate the adhesion quality of wafer layers. But, on the other hand, because of the quiet long acquisition time they need to perform one measurement, these setups remain shut in punctual measurement to evaluate global sample quality. This last point can lead to bad interpretation of the sample quality parameters, especially in the case of inhomogeneous samples. Asynchronous Optical Sampling (ASOPS) systems can perform sample characterization with picosecond acoustics up to 106 times faster than traditional pump-probe setups. This last point allows picosecond ultrasonic to unlock the acoustic imaging field at the nanometric scale to detect inhomogeneities regarding sample mechanical properties. This fact will be illustrated by presenting an image of the measured acoustical reflection coefficients obtained by mapping, with an ASOPS setup, a 255nm thin-film tungsten layer deposited on a silicone substrate. Interpretation of the coefficient reflection in terms of bounding quality adhesion will also be exposed. Origin of zones which exhibit good and bad quality bounding will be discussed.

Keywords: adhesion, picosecond ultrasonics, pump-probe, thin film

Procedia PDF Downloads 159

Authors: P. Donnelly, G. Mitchell

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Traumatic Brain Injury (TBI) is a major contributor to the global burden of disease; despite its ubiquity, there is significant variation in diagnosis, prognosis, and treatment between clinicians. This study aims to examine the spectrum of approaches that currently exist at a Level 1 Trauma Centre in Australasia by surveying Emergency Physicians and Neurosurgeons on those aspects of mTBI. A pilot survey of 17 clinicians (Neurosurgeons, Emergency Physicians, and others who manage patients with mTBI) at a Level 1 Trauma Centre in Brisbane, Australia, was conducted. The objective of this study was to examine the importance these clinicians place on various elements in their approach to the diagnosis, prognostication, and treatment of mTBI. The data were summarised, and the descriptive statistics reported. Loss of consciousness and post-traumatic amnesia were rated as the most important signs or symptoms in diagnosing mTBI (median importance of 8). MRI was the most important imaging modality in diagnosing mTBI (median importance of 7). ‘Number of the Previous TBIs’ and Intracranial Injury on Imaging’ were rated as the most important elements for prognostication (median importance of 9). Education and reassurance were rated as the most important modality for treating mTBI (median importance of 7). There was a statistically insignificant variation between the specialties as to the importance they place on each of these components. In this Australian tertiary trauma center, there appears to be variation in how clinicians approach mTBI. This study is underpowered to state whether this is between clinicians within a specialty or a trend between specialties. This variation is worthwhile in investigating as a step toward a unified approach to diagnosing, prognosticating, and treating this common pathology.

Keywords: mild traumatic brain injury, adult, clinician, survey

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Authors: Okhee Woo

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Purpose: With increasing concern of individual radiation exposure doses, studies analyzing radiation dosage in breast imaging modalities are required. Aim of this study is to compare radiation dosage and image quality between digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM). Methods and Materials: 303 patients (mean age 52.1 years) who studied DBT and FFDM were retrospectively reviewed. Radiation dosage data were obtained by radiation dosage scoring and monitoring program: Radimetrics (Bayer HealthCare, Whippany, NJ). Entrance dose and mean glandular doses in each breast were obtained in both imaging modalities. To compare the image quality of DBT with two-dimensional synthesized mammogram (2DSM) and FFDM, 5-point scoring of lesion clarity was assessed and the better modality between the two was selected. Interobserver performance was compared with kappa values and diagnostic accuracy was compared using McNemar test. The parameters of radiation dosages (entrance dose, mean glandular dose) and image quality were compared between two modalities by using paired t-test and Wilcoxon rank sum test. Results: For entrance dose and mean glandular doses for each breasts, DBT had lower values compared with FFDM (p-value < 0.0001). Diagnostic accuracy did not have statistical difference, but lesion clarity score was higher in DBT with 2DSM and DBT was chosen as a better modality compared with FFDM. Conclusion: DBT showed lower radiation entrance dose and also lower mean glandular doses to both breasts compared with FFDM. Also, DBT with 2DSM had better image quality than FFDM with similar diagnostic accuracy, suggesting that DBT may have a potential to be performed as an alternative to FFDM.

Keywords: radiation dose, DBT, digital mammography, image quality

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Authors: Bryony Davies

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Many cell and tissue culture practices ignore the effects of gravity on cell biology, and little is known about how cell components may move in response to gravitational forces. Starfish oocytes provide an excellent model for interrogating the movement of cell components due to their unusually large size, ease of handling, and high transparency. Chromosomes from starfish oocytes can be visualised by microinjection of the histone-H2B-mCherry plasmid into the oocytes. The movement of the chromosomes can then be tracked by live-cell fluorescence microscopy. The results from experiments using these methods suggest that there is a replicable downward movement of centrally located chromosomes at a median velocity of 0.39 μm/min. Chromosomes nearer the nuclear boundary showed more restricted movement. Chromosome density and shape could also be altered by microinjection of restriction enzymes, primarily Alu1, before imaging. This was found to alter the speed of chromosome movement, with chromosomes from Alu1-injected nuclei showing a median downward velocity of 0.60 μm/min. Overall, these results suggest that there is a non-negligible movement of chromosomes in response to gravitational forces and that this movement can be altered by enzyme activity. Future directions based on these results could interrogate if this observed downward movement extends to other cell components and to other cell types. Additionally, it may be important to understand whether gravitational orientation and vertical positioning of cell components alter cell behaviour. The findings here may have implications for current cell culture practices, which do not replicate cell orientations or external forces experienced in vivo. It is possible that a failure to account for gravitational forces in 2D cell culture alters experimental results and the accuracy of conclusions drawn from them. Understanding possible behavioural changes in cells due to the effects of gravity would therefore be beneficial.

Keywords: starfish, oocytes, live-cell imaging, microinjection, chromosome dynamics

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Authors: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

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Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression

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Authors: V. Durmus, M. Uydaci

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In order to prevent overburdened courts, rising costs of litigation, and lengthy trial resolutions, the Law on Mediation for Civil Disputes was enacted, which was aimed at defining the procedure and guiding principles for dispute resolutions under Civil Law, in 2012. This “Mediation Code” also applies for civil healthcare disputes in Turkey. Aside from mediation, reconciliation, governed by Articles 253-255 of Criminal Procedure Law, has emerged as an alternative way to resolve criminal medical disputes, but the difference between mediation and conciliation is mostly procedural. This article deals with mediation in Turkish health law and aspect of medical malpractice mediation in Turkey. In addition, this study examines the issue of mediation in health law from both a legal and normative point of view, including codes of mediation which regulate both the structural and professional practice of mediation providers. As a result, although there is not official record about success rate of medical malpractice litigations and malpractice mediation in Turkey, it is widely accepted that the success rate for medical malpractice cases is relatively low compared to other personal injury cases even if it is generally considered that medical malpractice case filings have gradually increased recently. According to the Justice Ministry’s Department of Mediation in Turkey, 719 civil disputes have referred to mediators since 2013 (when the first mediation law came into force) with a 98% success rate.

Keywords: malpractice mediation, medical disputes, reconciliation, health litigation, Turkish health law

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Authors: Yan-Lin Liu, Cheng-Ting Shih, Jay Wu

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Tablet devices have been introduced into the medical environment in recent years. The performance of display can be varied based on the use of different hardware specifications and types of display technologies. Therefore, the differences between tablet devices and medical diagnostic LCDs have to be verified to ensure that image quality is not jeopardized for clinical diagnosis in a picture archiving and communication system (PACS). In this study, a set of randomized object test patterns (ROTPs) were developed, which included randomly located spheres in abdominal CT images. Five radiologists were asked to independently review the CT images on different generations of iPads and a diagnostic monochrome medical LCD monitor. Receiver operating characteristic (ROC) analysis was performed by using a five-point rating scale, and the average area under curve (AUC) and average reading time (ART) were calculated. The AUC values for the second generation iPad, iPad mini, iPad Air, and monochrome medical monitor were 0.712, 0.717, 0.725, and 0.740, respectively. The differences between iPads were not significant. The ARTs were 177 min and 127 min for iPad mini and medical LCD monitor, respectively. A significant difference appeared (p = 0.04). The results show that the iPads were slightly inferior to the monochrome medical LCD monitor. However, tablet devices possess advantages in portability and versatility, which can improve the convenience of rapid diagnosis and teleradiology. With advances in display technology, the applicability of tablet devices and mobile devices may be more diversified in PACS.

Keywords: tablet devices, PACS, receiver operating characteristic, LCD monitor

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Authors: Gus Calderon, Richard McCreight, Tammy Schwartz

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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: Radka Obořilová, Hana Šimečková, Matěj Pastucha, Jan Přibyl, Petr Skládal, Ivana Mašlaňová, Zdeněk Farka

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Due to the spreading of antimicrobial resistance, alternative approaches to combat superinfections are being sought, both in the field of lysing agents and methods for studying bacterial lysis. A suitable alternative to antibiotics is phage therapy and enzybiotics, for which it is also necessary to study the mechanism of their action. Biosensor-based techniques allow rapid detection of pathogens in real time, verification of sensitivity to commonly used antimicrobial agents, and selection of suitable lysis agents. The detection of lysis takes place on the surface of the biosensor with immobilized bacteria, which has the potential to be used to study biofilms. An example of such a biosensor is surface plasmon resonance (SPR), which records the kinetics of bacterial lysis based on a change in the resonance angle. The bacteria are immobilized on the surface of the SPR chip, and the action of phage as the mass loss is monitored after a typical lytic cycle delay. Atomic force microscopy (AFM) is a technique for imaging of samples on the surface. In contrast to electron microscopy, it has the advantage of real-time imaging in the native conditions of the nutrient medium. In our case, Staphylococcus aureus was lysed using the enzyme lysostaphin and phage P68 from the familyPodoviridae at 37 ° C. In addition to visualization, AFM was used to study changes in mechanical properties during lysis, which resulted in a reduction of Young’s modulus (E) after disruption of the bacterial wall. Changes in E reflect the stiffness of the bacterium. These advanced methods provide deeper insight into bacterial lysis and can help to fight against bacterial diseases.

Keywords: biosensors, atomic force microscopy, surface plasmon resonance, bacterial lysis, staphylococcus aureus, phage P68

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Authors: Chin-Hsiang Lo, Wey Chia, Shih-Tien Hsu

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Introduction: Since 2016, the annual number of passengers on commercial flights at Taoyuan International Airport (TIA) has been ~40 million. Due to the outbreak and spread of COVID-19, the number of international flights sharply diminished in recent years. However, TIA is located at an East-Asian flight transportation junction; thus, many commercial and cargo flights continue service. When severe medical events happen on a commercial airliner, the decision to divert or not is based on consideration of both medical and operational issues. This study discusses the events related to the diversion of airplanes or reentry after taxiing for medical emergencies at Taoyuan International Airport. Background: We analyzed emergency medical records from the medical clinic of TIA from January 1, 2017, to December 31, 2022, for patients who needed emergency medical services but were unable to reach the airport clinic by themselves. We also collected data for patients treated after diversion from other airports or reentry after taxiing due to medical emergencies. Information such as when and where the event occurred, chief signs and symptoms, the tentative diagnosis (using the ICD-9-CM), management, and the sociodemographic features of the passengers were extracted from the medical records. Summary of Cases: TIA handled approximately 152 million passengers and 1,093,762 flights during the study period; a total of 2,804 emergencies occurred during this time period. Thirty-three medical emergencies warranted diversion (21 cases) or reentry (12 cases); 13 cases were diverted from Asia-Pacific flights and five from Asia-North America flights. The age of the passengers with diversion emergencies ranged from 2–85 years (mean, 46±20-years-old). Twenty-seven patients were transported to an emergency department, and four patients died. For all cases of diversion or reentry, the most common diagnoses were neurogenic problems (42.4%), Out-of-hospital cardiac arrest (OHCA) (15.2%), and cardiovascular problems (12.1%). Discussion: Most aircraft diversions were related to syncope, seizure, and OHCA. The decision to divert depends on medical and operational considerations. Emergency conditions are often serious; thus, improvement of the effectiveness of cooperation between airlines and medical teams remains a challenge.

Keywords: diversion, syncope, seizure, OHCA

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Authors: Tugba Sevinc Gamsiz, Emine Koroglu, Ozcan Keskin

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Aim: Nonalcoholic fatty liver disease (NAFLD) is considered the most common chronic liver disease in the general population. The higher mortality and morbidity among NAFLD patients and lack of symptoms makes early detection and management important. In our study, we aimed to evaluate the relationship between noninvasive imaging and biochemical markers in diabetic and nondiabetic patients diagnosed with NAFLD. Materials and Methods: The study was conducted from (September 2017) to (December 2017) on adults admitted to Internal Medicine and Gastroenterology outpatient clinics with hepatic steatosis reported on ultrasound or transient elastography within the last six months that exclude patients with other liver diseases or alcohol abuse. The data were collected and analyzed retrospectively. Number cruncher statistical system (NCSS) 2007 program was used for statistical analysis. Results: 116 patients were included in this study. Diabetic patients compared to nondiabetics had significantly higher Controlled Attenuation Parameter (CAP), Liver Stiffness Measurement (LSM) and fibrosis values. Also, hypertension, hepatomegaly, high BMI, hypertriglyceridemia, hyperglycemia, high A1c, and hyperuricemia were found to be risk factors for NAFLD progression to fibrosis. Advanced fibrosis (F3, F4) was present in 18,6 % of all our patients; 35,8 % of diabetic and 5,7 % of nondiabetic patients diagnosed with hepatic steatosis. Conclusion: Transient elastography is now used in daily clinical practice as an accurate noninvasive tool during follow-up of patients with fatty liver. Early diagnosis of the stage of liver fibrosis improves the monitoring and management of patients, especially in those with metabolic syndrome criteria.

Keywords: diabetes, elastography, fatty liver, fibrosis, metabolic syndrome

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Authors: Ghadeer Mohammad Said El-Sheikh, Samer Mohamad Shalhoob

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Medical equipment operation state is a valid reflection of health care organizations' performance, where such equipment highly contributes to the quality of healthcare services on several levels in which quality improvement has become an intrinsic part of the discourse and activities of health care services. In healthcare organizations, clinical and biomedical engineering departments play an essential role in maintaining the safety and efficiency of such equipment. One of the most challenging topics when it comes to such sophisticated equipment is the lifespan of medical equipment, where many factors will impact such characteristics of medical equipment through its life cycle. So far, many attempts have been made in order to address this issue where most of the approaches are kind of arbitrary approaches and one of the criticisms of existing approaches trying to estimate and understand the lifetime of a medical equipment lies under the inquiry of what are the environmental factors that can play into such a critical characteristic of a medical equipment. In an attempt to address this shortcoming, the purpose of our study rises where in addition to the standard technical factors taken into consideration through the decision-making process by a clinical engineer in case of medical equipment failure, the dimension of environmental factors shall be added. The investigations, researches and studies applied for the purpose of supporting the decision making process by a clinical engineers and assessing the lifespan of healthcare equipment’s in the Lebanese society was highly dependent on the identification of technical criteria’s that impacts the lifespan of a medical equipment where the affecting environmental factors didn’t receive the proper attention. The objective of our study is based on the need for introducing a new well-designed plan for evaluating medical equipment depending on two dimensions. According to this approach, the equipment that should be replaced or repaired will be classified based on a systematic method taking into account two essential criteria; the standard identified technical criteria and the added environmental criteria.

Keywords: technical, environmental, healthcare, characteristic of medical equipment

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Mohamed Ayeldeen, Abdelazim Negm

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Nowadays, strength characteristics of soils have more importance due to increasing building loads. In some projects, geotechnical properties of the soils are be improved using man-made materials varying from cement-based to chemical-based. These materials have proven successful in improving the engineering properties of the soil such as shear strength, compressibility, permeability, bearing capacity etc.. However, the use of these artificial injection formulas often modifies the pH level of soil, contaminates soil and groundwater. This is attributed to their toxic and hazardous characteristics. Recently, an environmentally friendly soil treatment method or Biological Treatment Method (BTM) was to bond particles of loose sandy soils. This research paper presents the preliminary results of using biopolymers for strengthening cohesionless soil. Xanthan gum was identified for further study over a range of concentrations varying from 0.25% to 2.00%. Xanthan gum is a polysaccharide secreted by the bacterium Xanthomonas campestris, used as a food additive and it is a nontoxic material. A series of direct shear, unconfined compressive strength, and permeability tests were carried out to investigate the behavior of sandy soil treated with Xanthan gum with different concentration ratios and at different curing times. Laser microscopy imaging was also conducted to study the microstructure of the treated sand. Experimental results demonstrated the compatibility of Xanthan gum to improve the geotechnical properties of sandy soil. Depending on the biopolymer concentration, it was observed that the biopolymers effectively increased the cohesion intercept and stiffness of the treated sand and reduced the permeability of sand. The microscopy imaging indicates that the cross-links of the biopolymers through and over the soil particles increase with the increase of the biopolymer concentration.

Keywords: biopolymer, direct shear, permeability, sand, shear strength, Xanthan gum

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Authors: Angely Sim Jia Wun, Sasa Arsovski

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Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Amlan Kumar Das, Avinash Marwal, Vikram Pareek

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Liposome plays an important role in medical and pharmaceutical science as e.g. nano scale drug carriers. Liposomes are vesicles of varying size consisting of a spherical lipid bilayer and an aqueous inner compartment. Magnet-driven liposome used for the targeted delivery of drugs to organs and tissues1. These liposome preparations contain encapsulated drug components and finely dispersed magnetic particles. Liposomes are vesicles of varying size consisting of a spherical lipid bilayer and an aqueous inner compartment that are generated in vitro. These are useful in terms of biocompatibility, biodegradability, and low toxicity, and can control biodistribution by changing the size, lipid composition, and physical characteristics2. Furthermore, liposomes can entrap both hydrophobic and hydrophilic drugs and are able to continuously release the entrapped substrate, thus being useful drug carriers. Magnetic liposomes (MLs) are phospholipid vesicles that encapsulate magneticor paramagnetic nanoparticles. They are applied as contrast agents for magnetic resonance imaging (MRI)3. The biological synthesis of nanoparticles using plant extracts plays an important role in the field of nanotechnology4. Green-synthesized magnetite nanoparticles-protein hybrid has been produced by treating Iron (III)/Iron(II) chloride with the leaf extract of Dhatura Inoxia. The phytochemicals present in the leaf extracts act as a reducing as well stabilizing agents preventing agglomeration, which include flavonoids, phenolic compounds, cardiac glycosides, proteins and sugars. The magnetite nanoparticles-protein hybrid has been trapped inside the aqueous core of the liposome prepared by reversed phase evaporation (REV) method using oleic and linoleic acid which has been shown to be driven under magnetic field confirming the formation magnetic liposome (ML). Chemical characterization of stealth magnetic liposome has been performed by breaking the liposome and release of magnetic nanoparticles. The presence iron has been confirmed by colour complex formation with KSCN and UV-Vis study using spectrophotometer Cary 60, Agilent. This magnet driven liposome using nanoparticles-protein hybrid can be a smart vesicles for the targeted drug delivery.

Keywords: nanoparticles-protein hybrid, magnetic liposome, medical, pharmaceutical science

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Authors: Szymon Szemik, Małgorzata Kowalska

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Objective: Medical students experience numerous demands during the education process, determining their quality of life (QoL) and health status. POLLEK (POLski LEKarz, eng. Polish Physician) study aims to identify and evaluate the quality of life, mental health status, and ever-recognized chronic diseases by simultaneously assessing their determinants in Polish medical students during long-term observation. Material and Methods: The POLLEK is the follow-up cohort study conducted among medical students at the Medical University of Silesia in Katowice. Students were followed during two observation periods: in their first year of studies, the academic year 2021/2022 (T1), and in their second year, the academic year 2022/2023 (T2). Results: The total number of participants in the first year of observation (T1) was 427 while in the second year (T2) was 335. Obtained results confirmed that the QoL score significantly decreased in their second year of studies mainly in the somatic and psychological domains. Moreover, we observed a significant increase in self-declared scoring of somatic symptoms year by year (from M=4.75 at T1 to M=8.06 at T2, p<0.001) in the GHQ-28 questionnaire survey. The determinants of QoL domains common to T1 and T2 remained self-declared health status, frequency of physical activity, and current financial situation. In the first year of evaluation, 56 students (13.10%) were overweight or obese, and 52 (15.8%) in the second. Regardless of the academic year, the increased risk of being overweight or obese was significantly associated with dissatisfaction with personal health, financial deficiencies, and a diet abundant in meat consumption. Conclusions: The QoL in medical students and selected determinants of their health status deteriorated during the observation period. Our findings suggest that medical schools should actively promote the activity needed to achieve a balance between schoolwork and the personal life of medical students from the beginning of university study.

Keywords: quality of life, mental health, medical students, follow-up study

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Authors: Mohammad Tahir Yousafzai, Nighat Nisar, Rehana Khalil

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The aim of this study is to assess the practices of sharp injuries and factors leading to it among medical practitioners in slum areas of Karachi, Pakistan. A cross sectional study was conducted in slum areas of Landhi Town Karachi. All medical practitioners (317) running the private clinics in the areas were asked to participate in the study. Data was collected on self administered pre-tested structured questionnaires. The frequency with percentage and 95% confidence interval was calculated for at least one sharp injury (SI) in the last one year. The factors leading to sharp injuries were assessed using multiple logistic regressions. About 80% of private medical practitioners consented to participate. Among these 87% were males and 13% were female. The mean age was 38±11 years and mean work experience was 12±9 years. The frequency of at least one sharp injury in the last one year was 27%(95% CI: 22.2-32). Almost 47% of Sharp Injuries were caused by needle recapping, less work experience, less than 14 years of schooling, more than 20 patients per day, administering more than 30 injections per day, reuse of syringes and needle recapping after use were significantly associated with sharp injuries. Injection practices were found inadequate among private medical practitioners in slum areas of Karachi, and the frequency of Sharp Injuries was found high in these areas. There is a risk of occupational transmission of blood borne infections among medical practitioners warranting an urgent need for launching awareness and training on standard precautions for private medical practitioners in the slum areas of Karachi.

Keywords: injection practices, private practitioners, sharp injuries, blood borne infections

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Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: Athicha Cherdpunt, Patompong Satapornpong

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The medical cannabis is made up of components also known as cannabinoids, which consists of two ingredients which are Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Interestingly, the Cannabinoid can be used for many treatments such as chemotherapy, including nausea and vomiting, cachexia, anorexia nervosa, spinal cord injury and disease, epilepsy, pain, and many others. However, the adverse drug reactions (ADRs) of THC can cause sedation, anxiety, dizziness, appetite stimulation and impairments in driving and cognitive function. Furthermore, genetic polymorphisms of CYP2C9, CYP2C19 and CYP3A4 influenced the THC metabolism and might be a cause of ADRs. Particularly, CYP2C19*17 allele increases gene transcription and therefore results in ultra-rapid metabolizer phenotype (UM). The aim of this study, is to investigate the frequency of CYP2C19*17 alleles in Thai patients who have been treated with medical cannabis. We prospectively enrolled 60 Thai patients who were treated with medical cannabis and clinical data from College of Pharmacy, Rangsit University. DNA of each patient was isolated from EDTA blood, using the Genomic DNA Mini Kit. CYP2C19*17 genotyping was conducted using the real time-PCR ViiA7 (ABI, Foster City, CA, USA). 30 patients with medical cannabis-induced ADRs group, 20 (67%) were female, and 10 (33%) were male, with an age range of 30-69 years. On the other hand, 30 patients without medical cannabis-induced ADRs (control group) consist of 17 (57%) female and 13 (43%) male. The most ADRs for medical cannabis treatment in the case group were dry mouth and dry throat (77%), tachycardia (70%), nausea (30%) and arrhythmia(10%). Accordingly, the case group carried CYP2C19*1/*1 (normal metabolizer) approximately 93%, while 7% patients carrying CYP2C19*1/*17 (ultra rapid metabolizers) exhibited in this group. Meanwhile, we found 90% of CYP2C19*1/*1 and 10% of CYP2C19*1/*17 in control group. In this study, we identified the frequency of CYP2C19*17 allele in Thai population which will support the pharmacogenetics biomarkers for screening and avoid ADRs of medical cannabis treatment.

Keywords: CYP2C19, allele frequency, ultra rapid metabolizer, medical cannabis

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Authors: Marwa Al-Subhi, Eiman Al-Ajmi, Mallak Al-Maamari, Humood Al-Dhuhli, Srinivasa Rao

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The orbit and its contents are affected by various pathologies and craniofacial anomalies. Sound knowledge of the normal orbital dimensions is clinically essential for successful surgical outcomes and also in the field of forensic anthropology. Racial, ethnic, and regional variations in the orbital dimensions have been reported. This study sought to determine the orbital dimensions of Omani subjects who had been referred for computed tomography (CT) images at a tertiary care hospital. A total of 273 patients’ CT images were evaluated retrospectively by using an electronic medical records database. The orbital dimensions were recorded using both axial and sagittal planes of CT images. The mean orbital index (OI) was found to be 83.25±4.83 and the prevalent orbital type was categorized as mesoseme. The mean orbital index was 83.34±5.05 and 83.16±4.57 in males and females, respectively, with their difference being statistically not significant (p=0.76). A statistically significant association was observed between the right and left orbits with regard to horizontal distance (p<0.05) and vertical distance (p<0.01) of orbit and OI (p<0.05). No significant difference between the OI and age groups was observed in both males and females. The mean interorbital distance and interzygomatic distance were found to be 19.45±1.52 mm and 95.59±4.08 mm, respectively. Both of these parameters were significantly higher in males (p<0.05). Results of the present study provide reference values of orbital dimensions in Omani subjects. The prevalent orbital type of Omani subjects is mesoseme, which is a hallmark of the white race.

Keywords: orbit, orbital index, mesoseme, ethnicity, variation

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Authors: Marcela De Oliveira, Marina P. Da Silva, Fernando C. G. Da Rocha, Jorge M. Santos, Jaime S. Cardoso, Paulo N. Lisboa-Filho

Abstract:

Multiple Sclerosis (MS) is an immune-mediated disease of the central nervous system characterized by neurodegeneration, inflammation, demyelination, and axonal loss. Magnetic resonance imaging (MRI), due to the richness in the information details provided, is the gold standard exam for diagnosis and follow-up of neurodegenerative diseases, such as MS. Brain atrophy, the gradual loss of brain volume, is quite extensive in multiple sclerosis, nearly 0.5-1.35% per year, far off the limits of normal aging. Thus, the brain volume quantification becomes an essential task for future analysis of the occurrence atrophy. The analysis of MRI has become a tedious and complex task for clinicians, who have to manually extract important information. This manual analysis is prone to errors and is time consuming due to various intra- and inter-operator variability. Nowadays, computerized methods for MRI segmentation have been extensively used to assist doctors in quantitative analyzes for disease diagnosis and monitoring. Thus, the purpose of this work was to evaluate the brain volume in MRI of MS patients. We used MRI scans with 30 slices of the five patients diagnosed with multiple sclerosis according to the McDonald criteria. The computational methods for the analysis of images were carried out in two steps: segmentation of the brain and brain volume quantification. The first image processing step was to perform brain extraction by skull stripping from the original image. In the skull stripper for MRI images of the brain, the algorithm registers a grayscale atlas image to the grayscale patient image. The associated brain mask is propagated using the registration transformation. Then this mask is eroded and used for a refined brain extraction based on level-sets (edge of the brain-skull border with dedicated expansion, curvature, and advection terms). In the second step, the brain volume quantification was performed by counting the voxels belonging to the segmentation mask and converted in cc. We observed an average brain volume of 1469.5 cc. We concluded that the automatic method applied in this work can be used for the brain extraction process and brain volume quantification in MRI. The development and use of computer programs can contribute to assist health professionals in the diagnosis and monitoring of patients with neurodegenerative diseases. In future works, we expect to implement more automated methods for the assessment of cerebral atrophy and brain lesions quantification, including machine-learning approaches. Acknowledgements: This work was supported by a grant from Brazilian agency Fundação de Amparo à Pesquisa do Estado de São Paulo (number 2019/16362-5).

Keywords: brain volume, magnetic resonance imaging, multiple sclerosis, skull stripper

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Authors: Ferdi Afian, Inne Yuliawati

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Background: The change in causes of death from infectious diseases to non-communicable diseases also occurs in the aviation community in Indonesia. Non-communicable diseases are influenced by several internal risk factors, such as age, lifestyle changes and the presence of other diseases. These risk factors will increase the incidence of heart diseases resulting in the incapacity of Indonesian aviators which will disrupt flight safety. Method: The study was conducted by collecting secondary data. The retrieval of primary data was obtained from medical records at the Indonesian Aviation Health Center in 2016-2017. The subjects in this study were all cases of incapacity in Indonesian aviators medical conditions. Results: In this study, there were 15 cases of aviators in Indonesia who experienced incapacity of medical conditions related to heart and lung diseases in 2016-2017. Based on the secondary data contained in the flight medical records at the Aviation Health Center Aviation, it was found that several factors related to aviators incapacity causing its inability to carried out flight duties. Conclusion: Incapacity of Indonesian aviators medical conditions are most affected by the high value of Body Mass Index (86%) and less affected by high of Uric Acid in the blood (26%) and Hyperglycemia (26%).

Keywords: incapacity, aviators, flight, Indonesia

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Authors: Sunday Oladele, Joseph Oluwagbeja Simeon

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Subsurface exploration, integrating methods of geotechnics and geophysics, of a planned construction site in the coastal city of Lagos, Nigeria has been carried out with the aim of characterizing the soil properties and their implication for the proposed infrastructural development. Six Standard Penetration Tests (SPT), fourteen Dutch Cone Penetrometer Tests (DCPT) and 2D Electrical Resistivity Imaging employing Dipole-dipole and Pole-dipole arrays were implemented on the site. The topsoil (0 - 4m) consists of highly compacted sandy lateritic clay(10 to 5595Ωm) to 1.25m in some parts and dense sand in other parts to 5.50m depth. This topsoil was characterized as a material of very high shear strength (≤ 150kg/m2) and allowable bearing pressure value of 54kN/m2 to 85kN/m2 and a safety factor of 2.5. Soft amorphous peat/peaty clay (0.1 to 11.4Ωm), 3-6m thick, underlays the lateritic clay to about 18m depth. Grey, medium dense to very dense sand (0.37 to 2387Ωm) with occasional gravels underlies the peaty clay down to 30m depth. Within this layer, the freshwater bearing zones are characterized by high resistivity response (83 to 2387Ωm), while the clayey sand/saline water intruded sand produced subdued resistivity output (0.37 to 40Ωm). The overall ground-bearing pressure for the proposed structure would be 225kN/m2. Bored/cast-in-place pile at 18.00m depth with any of these diameters and respective safe working loads 600mm/1,140KN, 800mm/2,010KN and 1000mm/3,150KN is recommended for the proposed multi-story structure.

Keywords: subsurface exploration, Geotechnical properties, resistivity imaging, pile

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Authors: Naim Izet Kajtazi

Abstract:

Context: Although rare, glomus tumor (i.e., nonchromaffin chemodectomas and paragan¬gliomas) is the most common middle ear tumor, with female predominance. Pre-operative embolization is often required to devascularize the hypervascular tumor for better surgical outcomes. Process: A 35-year-old female presented with episodes of frequent dizziness, ear fullness, and right ear tinnitus for 12 months. Head imaging revealed a right glomus tympanicum tumor. She underwent pre-operative endovascular embolization of the glomus tympanicum tumor with surgical, cyanoacrylate-based glue. Immediately after the procedure, she developed drowsiness and severe pain in the right temporal region. Further investigations revealed a right cerebellar stroke in the posterior inferior cerebellar artery territory. She was treated with intravenous heparin, followed by one year of oral anticoagulation. With rehabilitation, she significantly recovered from her post embolization stroke. However, the tumor was resected at another institution. Ten years later, follow-up imaging indicated a gradual increase in the size of the glomus jugulare tumor, compressing the nearby critical vascular structures. She subsequently received radiation therapy to treat the residual tumor. Outcome: Currently, she has no neurological deficit, but her mild dizziness, right ear tinnitus, and hearing impairment persist. Relevance: This case highlights the complex nature of these tumors, which often bring challenges to the patients as well as treatment teams. The multi-disciplinary team approach is necessary to tailor the management plan for individual tumors. Although embolization is a safe procedure, careful attention and thoughtful anatomic knowledge regarding dangerous anastomosis are essential to avoid devastating complications. Complications occur due to encountered vessel anomalies and new anastomoses formed during the gluing and changes in hemodynamics.

Keywords: stroke, embolization, MRI brain, cerebral angiogram

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Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

Abstract:

Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

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Authors: Ainouna Bouziane

Abstract:

The ability of Electron Tomography to recover the 3D structure of catalysts, with spatial resolution in the subnanometer scale, has been widely explored and reviewed in the last decades. A variety of experimental techniques, based either on Transmission Electron Microscopy (TEM) or Scanning Transmission Electron Microscopy (STEM) have been used to reveal different features of nanostructured catalysts in 3D, but High Angle Annular Dark Field imaging in STEM mode (HAADF-STEM) stands out as the most frequently used, given its chemical sensitivity and avoidance of imaging artifacts related to diffraction phenomena when dealing with crystalline materials. In this regard, our group has developed a methodology that combines image denoising by undecimated wavelet transforms (UWT) with automated, advanced segmentation procedures and parameter selection methods using CS-TVM (Compressed Sensing-total variation minimization) algorithms to reveal more reliable quantitative information out of the 3D characterization studies. However, evaluating the accuracy of the magnitudes estimated from the segmented volumes is also an important issue that has not been properly addressed yet, because a perfectly known reference is needed. The problem particularly complicates in the case of multicomponent material systems. To tackle this key question, we have developed a methodology that incorporates volume reconstruction/segmentation methods. In particular, we have established an approach to evaluate, in quantitative terms, the accuracy of TVM reconstructions, which considers the influence of relevant experimental parameters like the range of tilt angles, image noise level or object orientation. The approach is based on the analysis of material-realistic, 3D phantoms, which include the most relevant features of the system under analysis.

Keywords: electron tomography, supported catalysts, nanometrology, error assessment

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Authors: Andrew N. Saylor, James R. Peters

Abstract:

Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

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