452 citations · 761 across the 21 of their papers we have counts for
12 papers · 1 filter
Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations
Aaron S. Coyner, Praveer Singh, James M. Brown +5
Background: Artificial intelligence (AI) may demonstrate racial bias when skin or choroidal pigmentation is present in medical images. Recent studies have shown that convolutional…
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
Ujjwal Baid, Satyam Ghodasara, Suyash Mohan +100
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR)…
Towards Trainable Saliency Maps in Medical Imaging
Mehak Aggarwal, Nishanth Arun, Sharut Gupta +9
While success of Deep Learning (DL) in automated diagnosis can be transformative to the medicinal practice especially for people with little or no access to doctors, its widespread…
Assessing the validity of saliency maps for abnormality localization in medical imaging
Nishanth Thumbavanam Arun, Nathan Gaw, Praveer Singh +5
Saliency maps have become a widely used method to assess which areas of the input image are most pertinent to the prediction of a trained neural network. However, in the context of…
ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations
Vivek Sharma, Praneeth Vepakomma, Tristan Swedish +3
Recently, there has been the development of Split Learning, a framework for distributed computation where model components are split between the client and server (Vepakomma et al.…
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
Bruno Lecouat, Ken Chang, Chuan-Sheng Foo +7
Supervised deep learning algorithms have enabled significant performance gains in medical image classification tasks. But these methods rely on large labeled datasets that require…