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SAM3D: Segment Anything Model in Volumetric Medical Images
March 7, 2024, 5:46 a.m. | Nhat-Tan Bui, Dinh-Hieu Hoang, Minh-Triet Tran, Gianfranco Doretto, Donald Adjeroh, Brijesh Patel, Arabinda Choudhary, Ngan Le
cs.CV updates on arXiv.org arxiv.org
Abstract: Image segmentation remains a pivotal component in medical image analysis, aiding in the extraction of critical information for precise diagnostic practices. With the advent of deep learning, automated image segmentation methods have risen to prominence, showcasing exceptional proficiency in processing medical imagery. Motivated by the Segment Anything Model (SAM)-a foundational model renowned for its remarkable precision and robust generalization capabilities in segmenting 2D natural images-we introduce SAM3D, an innovative adaptation tailored for 3D volumetric medical …
arxiv cs.cv eess.iv images medical segment segment anything segment anything model type
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