5 citations · 11 across the 7 of their papers we have counts for
4 papers · 1 filter
Taming the Tail: Leveraging Asymmetric Loss and Pade Approximation to Overcome Medical Image Long-Tailed Class Imbalance
Pankhi Kashyap, Pavni Tandon, Sunny Gupta +3
Long-tailed problems in healthcare emerge from data imbalance due to variability in the prevalence and representation of different medical conditions, warranting the requirement of…
MedSAGa: Few-shot Memory Efficient Medical Image Segmentation using Gradient Low-Rank Projection in SAM
Navyansh Mahla, Annie D'souza, Shubh Gupta +2
The application of large-scale models in medical image segmentation demands substantial quantities of meticulously annotated data curated by experts along with high computational r…
FESS Loss: Feature-Enhanced Spatial Segmentation Loss for Optimizing Medical Image Analysis
Charulkumar Chodvadiya, Navyansh Mahla, Kinshuk Gaurav Singh +1
Medical image segmentation is a critical process in the field of medical imaging, playing a pivotal role in diagnosis, treatment, and research. It involves partitioning of an image…
INSITE: labelling medical images using submodular functions and semi-supervised data programming
Akshat Gautam, Anurag Shandilya, Akshit Srivastava +3
The necessity of large amounts of labeled data to train deep models, especially in medical imaging creates an implementation bottleneck in resource-constrained settings. In Insite…