Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
Bruno Lecouat, Pavitra Krishnaswamy(Agency for Science, Technology and Research), James M. Brown(Mary Lyon Centre at MRC Harwell), Balagopal Unnikrishnan(Agency for Science, Technology and Research), Houssam Zenati(Agency for Science, Technology and Research), Jayashree Kalpathy–Cramer(University of Colorado Denver), Ken Chang(Harvard University), Chuan-Sheng Foo(Institute for Infocomm Research), Vijay Chandrasekhar(Agency for Science, Technology and Research), Andrew Beers(Massachusetts General Hospital)
Cited by 30
Related Papers
3D Slicer as an image computing platform for the Quantitative Imaging Network
|Magnetic Resonance Imaging|2012|9.1k
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
|IEEE Transactions on Medical Imaging|2014|6.7k
High-throughput discovery of novel developmental phenotypes
|Nature|2016|1.3k
Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials
|Neuro-Oncology|2015|670
Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks
|JAMA Ophthalmology|2018|660