192 citations · 729 across the 35 of their papers we have counts for
14 papers · 1 filter
Signed Input Regularization
Saeid Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh
Over-parameterized deep models usually over-fit to a given training distribution, which makes them sensitive to small changes and out-of-distribution samples at inference time, lea…
Artificial Intelligence in Glioma Imaging: Challenges and Advances
Weina Jin, Mostafa Fatehi, Kumar Abhishek +3
Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these les…
Deep Learning Models for Digital Pathology
Aïcha BenTaieb, Ghassan Hamarneh
Histopathology images; microscopy images of stained tissue biopsies contain fundamental prognostic information that forms the foundation of pathological analysis and diagnostic med…
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI
Shahab Aslani, Vittorio Murino, Michael Dayan +3
This paper presents a simple and effective generalization method for magnetic resonance imaging (MRI) segmentation when data is collected from multiple MRI scanning sites and as a…
Deep Semantic Segmentation of Natural and Medical Images: A Review
Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen +2
The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class. This task is a part of the concept…
WhiteNNer-Blind Image Denoising via Noise Whiteness Priors
Saeed Izadi, Zahra Mirikharaji, Mengliu Zhao +1
The accuracy of medical imaging-based diagnostics is directly impacted by the quality of the collected images. A passive approach to improve image quality is one that lags behind i…