11 citations · 13 across the 5 of their papers we have counts for
5 papers
SymmAdapt: Symmetrical Flow Matching for Source-Free Domain Adaptation in Medical Image Segmentation
Tal Grossman, Noa Cahan, Hayit Greenspan
Domain shift across imaging modalities and acquisition sites remains a significant barrier to the clinical deployment of segmentation models. Source-free unsupervised domain adapta…
DiffuSAM: Diffusion-Based Prompt-Free SAM2 for Few-Shot and Source-Free Medical Image Segmentation
Tal Grossman, Noa Cahan, Lev Ayzenberg +1
Segmentation models such as Segment Anything Model (SAM) and SAM2 achieve strong prompt-driven zero-shot performance. However, their training on natural images limits domain transf…
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…
Weakly Supervised Attention Model for RV StrainClassification from volumetric CTPA Scans
Noa Cahan, Edith M. Marom, Shelly Soffer +4
Pulmonary embolus (PE) refers to obstruction of pulmonary arteries by blood clots. PE accounts for approximately 100,000 deaths per year in the United States alone. The clinical pr…
Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction
Koby Bibas, Gili Weiss-Dicker, Dana Cohen +2
Cryo-Electron Microscopy (Cryo-EM) is a Nobel prize-winning technology for determining the 3D structure of particles at near-atomic resolution. A fundamental step in the recovering…