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Carcino-Net: A Deep Learning Framework for Automated Gleason Grading of Prostate Biopsies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Gleason scoring for prostate cancer grading is a subjective examination and suffers from suboptimal interobserver and intraobserver variability. To overcome these limitations, we have developed an automated system to grade prostate biopsies. We prese...
Reproducibility of Results Biopsy Male Humans Deep Learning Neoplasm Grading
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Lung CT Image Registration through Landmark-constrained Learning with Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Accurate registration of lung computed tomography (CT) image is a significant task in thorax image analysis. Recently deep learning-based medical image registration methods develop fast and achieve promising performance on accuracy and speed. However...
Tomography, X-Ray Computed Lung Neural Networks, Computer Thorax
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Evaluating Deep Learning Algorithms in Pulmonary Nodule Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Lung cancer is considered the deadliest cancer worldwide. In order to detect it, radiologists need to inspect multiple Computed Tomography (CT) scans. This task is tedious and time consuming. In recent years, promising methods based on deep learning ...
Deep Learning Lung Neoplasms Software Tomography, X-Ray Computed Algorithms Humans
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Metal Artifacts Reduction in CT Scans using Convolutional Neural Network with Ground Truth Elimination.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Metal artifacts are very common in CT scans since metal insertion or replacement is performed for enhancing certain functionality or mechanism of patient's body. These streak artifacts could degrade CT image quality severely, and consequently, they c...
Humans Tomography, X-Ray Computed Neural Networks, Computer Artifacts Radionuclide Imaging Metals
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Locate the Superficial Femoral Artery with Occlusion by Deep Neural Network Correcting Interpolation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
In clinical practice, doctors usually use computed tomography angiography (CTA) to examine lower extremity atherosclerotic occlusive (ASO). Conveniently and accurately locating occlusive superficial femoral artery (SFA) which is difficult to extract ...
Thigh Neural Networks, Computer Computed Tomography Angiography Angiography Femoral Artery
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Malocclusion Classification on 3D Cone-Beam CT Craniofacial Images Using Multi-Channel Deep Learning Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Analyzing and interpreting cone-beam computed tomography (CBCT) images is a complicated and often time-consuming process. In this study, we present two different architectures of multi-channel deep learning (DL) models: "Ensemble" and "Synchronized m...
Cone-Beam Computed Tomography Malocclusion Imaging, Three-Dimensional Humans Deep Learning
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Volumetric Choroidal Segmentation Using Sequential Deep Learning Approach in High Myopia Subjects.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Many ocular diseases are associated with choroidal changes. Therefore, it is crucial to be able to segment the choroid to study its properties. Previous methods for choroidal segmentation have focused on single cross-sectional scans. Volumetric choro...
Cross-Sectional Studies Myopia Humans Tomography, Optical Coherence Choroid Deep Learning
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MDL-IWS: Multi-view Deep Learning with Iterative Watershed for Pulmonary Fissure Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Pulmonary fissure segmentation is important for localization of lung lesions which include nodules at respective lobar territories. This can be very useful for diagnosis as well as treatment planning. In this paper, we propose a novel coarse-to-fine ...
Algorithms Pleural Cavity Lung Deep Learning Tomography, X-Ray Computed
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Deep Learning Based Lung Region Segmentation with Data Preprocessing by Generative Adversarial Nets.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
In endoscopic surgery, it is necessary to understand the three-dimensional structure of the target region to improve safety. For organs that do not deform much during surgery, preoperative computed tomography (CT) images can be used to understand the...
Deep Learning Endoscopy Lung Tomography, X-Ray Computed
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Y-Net for Chest X-Ray Preprocessing: Simultaneous Classification of Geometry and Segmentation of Annotations.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Over the last decade, convolutional neural networks (CNNs) have emerged as the leading algorithms in image classification and segmentation. Recent publication of large medical imaging databases have accelerated their use in the biomedical arena. Whil...
Neural Networks, Computer Radiography X-Rays Algorithms Machine Learning
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