17 citations · 17 across the 4 of their papers we have counts for
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Synthetic Volumetric Data Generation Enables Zero-Shot Generalization of Foundation Models in 3D Medical Image Segmentation
Satrajit Chakrabarty, Sourya Sengupta, Gopal Avinash +1
Foundation models such as Segment Anything Model 2 (SAM 2) exhibit strong generalization on natural images and videos but perform poorly on medical data due to differences in appea…
Comparing SAM 2 and SAM 3 for Zero-Shot Segmentation of 3D Medical Data
Satrajit Chakrabarty, Ravi Soni
Foundation models, such as the Segment Anything Model (SAM), have heightened interest in promptable zero-shot segmentation. Although these models perform strongly on natural images…
SynthFM: Training Modality-agnostic Foundation Models for Medical Image Segmentation without Real Medical Data
Sourya Sengupta, Satrajit Chakrabarty, Keerthi Sravan Ravi +2
Foundation models like the Segment Anything Model (SAM) excel in zero-shot segmentation for natural images but struggle with medical image segmentation due to differences in textur…
Is SAM 2 Better than SAM in Medical Image Segmentation?
Sourya Sengupta, Satrajit Chakrabarty, Ravi Soni
The Segment Anything Model (SAM) has demonstrated impressive performance in zero-shot promptable segmentation on natural images. The recently released Segment Anything Model 2 (SAM…