13 citations · 17 across the 7 of their papers we have counts for
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Few-Shot Concept Prompt Learning for Segmentation Foundation Models via Visual Grounding
Rahul Venkataramani, Rachana Sathish
Promptable segmentation foundation models (FMs) such as SAM3 and Medical SAM3 promise few-shot, interactively-specified segmentation for medical imaging through a natural language…
Synthetic Simplicity: Unveiling Bias in Medical Data Augmentation
Krishan Agyakari Raja Babu, Rachana Sathish, Mrunal Pattanaik +1
Synthetic data is becoming increasingly integral in data-scarce fields such as medical imaging, serving as a substitute for real data. However, its inherent statistical characteris…
Task-driven Prompt Evolution for Foundation Models
Rachana Sathish, Rahul Venkataramani, K S Shriram +1
Promptable foundation models, particularly Segment Anything Model (SAM), have emerged as a promising alternative to the traditional task-specific supervised learning for image segm…
Fully Convolutional Neural Network for Semantic Segmentation of Anatomical Structure and Pathologies in Colour Fundus Images Associated with Diabetic Retinopathy
Oindrila Saha, Rachana Sathish, Debdoot Sheet
Diabetic retinopathy (DR) is the most common form of diabetic eye disease. Retinopathy can affect all diabetic patients and becomes particularly dangerous, increasing the risk of b…