Computers in Biology and Medicine
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#1Ali Kabiri (TMU: Tarbiat Modares University)H-Index: 4
#2Gholamhossein Liaghat (TMU: Tarbiat Modares University)H-Index: 20
Last. Fatemeh Alavi (TMU: Tarbiat Modares University)H-Index: 4
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Abstract Little is known about the impact behavior of composite fixation plate used in the fracture healing of long bones diaphysis. Hence, this study examined polypropylene composite fixation plates using different glass fibers and measured their biomechanical responses under axial impact loading experimentally and numerically. Short randomly oriented, long unidirectional prepregs and fiber yarn of glass were considered as reinforcements, and fixation plates were fabricated through two differen...
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#1Eliott Brion (UCL: Université catholique de Louvain)H-Index: 3
#2Jean Léger (UCL: Université catholique de Louvain)H-Index: 2
Last. Benoît Macq (UCL: Université catholique de Louvain)H-Index: 47
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Abstract In radiation therapy, a CT image is used to manually delineate the organs and plan the treatment. During the treatment, a cone beam CT (CBCT) is often acquired to monitor the anatomical modifications. For this purpose, automatic organ segmentation on CBCT is a crucial step. However, manual segmentations on CBCT are scarce, and models trained with CT data do not generalize well to CBCT images. We investigate adversarial networks and intensity-based data augmentation, two strategies lever...
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#1Rabiah Al-qudah (Concordia University)H-Index: 1
#1Rabiah Al-qudah (CUW: Concordia University Wisconsin)
Last. Ching Y. Suen (Concordia University)H-Index: 58
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Abstract Peripheral Blood Smear (PBS) analysis is a vital routine test carried out by medical specialists to assess some health aspects of individuals. The automation of blood analysis has attracted the attention of researchers in recent years, as it will not only save time, money and reduce errors, but also protect and save lives of front-line workers, especially during pandemics. In this work, deep neural networks are trained on a synthetic blood smears dataset to classify fifteen different wh...
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#1Ricardo R. Lopes (UvA: University of Amsterdam)H-Index: 4
#2Hidde Bleijendaal (UvA: University of Amsterdam)H-Index: 3
Last. Henk A. Marquering (UvA: University of Amsterdam)H-Index: 33
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Abstract The pathogenic mutation p.Arg14del in the gene encoding Phospholamban (PLN) is known to cause cardiomyopathy and leads to increased risk of sudden cardiac death. Automatic tools might improve the detection of patients with this rare disease. Deep learning is currently the state-of-the-art in signal processing but requires large amounts of data to train the algorithms. In situations with relatively small amounts of data, like PLN, transfer learning may improve accuracy. We propose an ECG...
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#1Konstantina Kourou (FORTH: Foundation for Research & Technology – Hellas)H-Index: 4
Last. Dimitrios I. Fotiadis (FORTH: Foundation for Research & Technology – Hellas)H-Index: 53
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Abstract Displaying resilience following a diagnosis of breast cancer is crucial for successful adaptation to illness, well-being, and health outcomes. Several theoretical and computational models have been proposed toward understanding the complex process of illness adaptation, involving a large variety of patient sociodemographic, lifestyle, medical, and psychological characteristics. To date, conventional multivariate statistical methods have been used extensively to model resilience. In the ...
1 CitationsSource
#1Leila Abdelrahman (UM: University of Miami)H-Index: 3
#2Manal Al Ghamdi (UQU: Umm al-Qura University)H-Index: 5
Last. Mohamed Abdel-Mottaleb (UM: University of Miami)H-Index: 37
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Abstract Despite its proven record as a breast cancer screening tool, mammography remains labor-intensive and has recognized limitations, including low sensitivity in women with dense breast tissue. In the last ten years, Neural Network advances have been applied to mammography to help radiologists increase their efficiency and accuracy. This survey aims to present, in an organized and structured manner, the current knowledge base of convolutional neural networks (CNNs) in mammography. The surve...
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#1Matthieu MartinH-Index: 3
#2Bruno Sciolla (UCBL: Claude Bernard University Lyon 1)
Last. Philippe DelachartreH-Index: 16
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#1Albert Swiecicki (Duke University)
#2Nianyi Li (Duke University)
Last. Maciej A. Mazurowski (Duke University)H-Index: 24
view all 8 authors...
Abstract A fully-automated deep learning algorithm matched performance of radiologists in assessment of knee osteoarthritis severity in radiographs using the Kellgren-Lawrence grading system. Purpose To develop an automated deep learning-based algorithm that jointly uses Posterior-Anterior (PA) and Lateral (LAT) views of knee radiographs to assess knee osteoarthritis severity according to the Kellgren-Lawrence grading system. Materials and Methods We used a dataset of 9739 exams from 2802 patien...
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#1Mai Gamal (Nile University)
#2Mohamed H. Mousa (Wright State University)H-Index: 1
Last. Sherif M. Elbasiouny (Wright State University)H-Index: 12
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Abstract Up to 50% of amputees abandon their prostheses, partly due to rapid degradation of the control systems, which require frequent recalibration. The goal of this study was to develop a Kalman filter-based approach to decoding motoneuron activity to identify movement kinematics and thereby provide stable, long-term, accurate, real-time decoding. The Kalman filter-based decoder was examined via biologically varied datasets generated from a high-fidelity computational model of the spinal moto...
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#1Amirreza Mahbod (Medical University of Vienna)H-Index: 7
#2Gerald Schaefer (Lboro: Loughborough University)H-Index: 31
Last. Isabella Ellinger (Medical University of Vienna)H-Index: 17
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Abstract Nuclei instance segmentation plays an important role in the analysis of hematoxylin and eosin (H&E)-stained images. While supervised deep learning (DL)-based approaches represent the state-of-the-art in automatic nuclei instance segmentation, annotated datasets are required to train these models. There are two main types of tissue processing protocols resulting in formalin-fixed paraffin-embedded samples (FFPE) and frozen tissue samples (FS), respectively. Although FFPE-derived H&E stai...
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