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ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models
Lev Ayzenberg, Raja Giryes, Hayit Greenspan
This work introduces a new framework, ProtoSAM, for one-shot medical image segmentation. It combines the use of prototypical networks, known for few-shot segmentation, with SAM - a…
X-ray2CTPA: Leveraging Diffusion Models to Enhance Pulmonary Embolism Classification
Noa Cahan, Eyal Klang, Galit Aviram +4
Chest X-rays or chest radiography (CXR), commonly used for medical diagnostics, typically enables limited imaging compared to computed tomography (CT) scans, which offer more detai…
DINOv2 based Self Supervised Learning For Few Shot Medical Image Segmentation
Lev Ayzenberg, Raja Giryes, Hayit Greenspan
Deep learning models have emerged as the cornerstone of medical image segmentation, but their efficacy hinges on the availability of extensive manually labeled datasets and their a…