3 citations · 3 across the 3 of their papers we have counts for
3 papers
Correcting Class Imbalances with Self-Training for Improved Universal Lesion Detection and Tagging
Alexander Shieh, Tejas Sudharshan Mathai, Jianfei Liu +2
Universal lesion detection and tagging (ULDT) in CT studies is critical for tumor burden assessment and tracking the progression of lesion status (growth/shrinkage) over time. Howe…
3D Universal Lesion Detection and Tagging in CT with Self-Training
Jared Frazier, Tejas Sudharshan Mathai, Jianfei Liu +2
Radiologists routinely perform the tedious task of lesion localization, classification, and size measurement in computed tomography (CT) studies. Universal lesion detection and tag…
Few-shot Diagnosis of Chest x-rays Using an Ensemble of Random Discriminative Subspaces
Kshitiz, Garvit Garg, Angshuman Paul
Due to the scarcity of annotated data in the medical domain, few-shot learning may be useful for medical image analysis tasks. We design a few-shot learning method using an ensembl…