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Prediction of Multiple Sclerosis Patient Disability from Structural Connectivity using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Prediction of disability progression in multiple sclerosis patients is a critical component of their management. In particular, one challenge is to identify and characterize a patient profile who may benefit of efficient treatments. However, it is no...
Gray Matter Neural Networks, Computer Brain Disability Evaluation Humans Image Processing, Computer-Assisted Multiple Sclerosis Magnetic Resonance Imaging
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Hand and Object Segmentation from Depth Image using Fully Convolutional 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, 2019
Semantic segmentation is an important step for hand and object tracking as subsequent tracking algorithms depend heavily on the accuracy of the segmented hand and object. However, current methods for hand and object segmentation are limited in the nu...
Movement Neural Networks, Computer Algorithms Humans Hand Biomechanical Phenomena Semantics Image Processing, Computer-Assisted
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Deep Learning Classification Models Built with Two-step Transfer Learning for Age Related Macular Degeneration Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The objective of this study was to build deep learning models with optical coherence tomography (OCT) images to classify normal and age related macular degeneration (AMD), AMD with fluid, and AMD without any fluid. In this study, 185 normal OCT image...
ROC Curve Tomography, Optical Coherence Macular Degeneration Computer Simulation Deep Learning Humans
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An Interpretable Ensemble Deep Learning Model for Diabetic Retinopathy Disease Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Diabetic retinopathy (DR) is one kind of eye disease that is caused by overtime diabetes. Lots of patients around the world suffered from DR which may bring about blindness. Early detection of DR is a rigid quest which can remind the DR patients to s...
Humans Fundus Oculi Deep Learning Diabetic Retinopathy Diabetes Mellitus Algorithms
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Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
We describe and assess convolutional neural network (CNN) models for detection of glaucoma based upon optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability maps. CNNs pretrained on natural images performed comparably to CNNs...
Nerve Fibers Tomography, Optical Coherence Probability ROC Curve Humans Neural Networks, Computer Glaucoma
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Conditional Adversarial Transfer for Glaucoma Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Deep learning has achieved great success in image classification task when given sufficient labeled training images. However, in fundus image based glaucoma diagnosis, we often have very limited training data due to expensive cost in data labeling. M...
Fundus Oculi Image Interpretation, Computer-Assisted Humans Glaucoma Deep Learning
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Depthwise Separable Convolutional Neural Network Model for Intra-Retinal Cyst 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, 2019
Intra-retinal cysts (IRCs) are significant in detecting several ocular and retinal pathologies. Segmentation and quantification of IRCs from optical coherence tomography (OCT) scans is a challenging task due to present of speckle noise and scan inten...
Humans Neural Networks, Computer Retina Retinal Diseases Tomography, Optical Coherence Cysts
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Body-Mounted MRI-Conditional Parallel Robot for Percutaneous Interventions Structural Improvement, Calibration, and Accuracy Analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
To assist in percutaneous interventions in the lower back under magnetic resonance imaging guidance, a 4 degree-of-freedom body-mounted parallel robot is developed. The robot structure is improved comparatively to a previously developed robot, to inc...
Administration, Cutaneous Calibration Magnetic Resonance Imaging Robotics
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Shoulder-mounted Robot for MRI-Guided Arthrography: Clinically Optimized System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
This paper introduces our compact and lightweight patient-mounted MRI-compatible 4 degree-of-freedom (DOF) robot with an improved transmission system for MRI-guided arthrography procedures. This robot could make the traditional two-stage arthrography...
Phantoms, Imaging Arthrography Humans Magnetic Resonance Imaging Robotics Shoulder
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Convolutional Recurrent Neural Networks to Characterize the Circulation Component in the Thoracic Impedance during Out-of-Hospital Cardiac Arrest.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Pulse detection during out-of-hospital cardiac arrest remains challenging for both novel and expert rescuers because current methods are inaccurate and time-consuming. There is still a need to develop automatic methods for pulse detection, where the ...
Humans Neural Networks, Computer Cardiopulmonary Resuscitation Out-of-Hospital Cardiac Arrest Electric Impedance Pulse
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