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01/20/2023
On Retrospective k-space Subsampling schemes For Deep MRI Reconstruction
Purpose: The MRI k-space acquisition is time consuming. Traditional tech...
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04/05/2022
A deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography
Purpose - To develop and validate a deep learning (DL) framework for the...
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11/18/2021
Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction
Magnetic Resonance Imaging can produce detailed images of the anatomy an...
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08/17/2021
Deep MRI Reconstruction with Radial Subsampling
In spite of its extensive adaptation in almost every medical diagnostic ...
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09/21/2020
Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study
Amidst the ongoing pandemic, several studies have shown that COVID-19 cl...
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10/16/2019
Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks
Interpretability of deep learning (DL) systems is gaining attention in m...
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08/15/2019
A deep learning model for segmentation of geographic atrophy to study its long-term natural history
Purpose: To develop and validate a deep learning model for automatic seg...
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03/22/2019