15 citations · 48 across the 9 of their papers we have counts for
4 papers · 1 filter
Self-training of Machine Learning Models for Liver Histopathology: Generalization under Clinical Shifts
Jin Li, Deepta Rajan, Chintan Shah +7
Histopathology images are gigapixel-sized and include features and information at different resolutions. Collecting annotations in histopathology requires highly specialized pathol…
Self-Training with Improved Regularization for Sample-Efficient Chest X-Ray Classification
Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris +1
Automated diagnostic assistants in healthcare necessitate accurate AI models that can be trained with limited labeled data, can cope with severe class imbalances and can support si…
Leveraging Medical Visual Question Answering with Supporting Facts
Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade +2
In this working notes paper, we describe IBM Research AI (Almaden) team's participation in the ImageCLEF 2019 VQA-Med competition. The challenge consists of four question-answering…
Kernel Sparse Models for Automated Tumor Segmentation
Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan +3
In this paper, we propose sparse coding-based approaches for segmentation of tumor regions from MR images. Sparse coding with data-adapted dictionaries has been successfully employ…