MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation-Reference-Cited by-同舟云学术

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MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation

Published:2024-12 Issue: Volume:98 Page:103310
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Chen Cheng^ORCID,Miao Juzheng^ORCID,Wu Dufan^ORCID,Zhong Aoxiao^ORCID,Yan Zhiling,Kim Sekeun^ORCID,Hu Jiang^ORCID,Liu Zhengliang^ORCID,Sun Lichao,Li Xiang^ORCID,Liu Tianming^ORCID,Heng Pheng-Ann^ORCID,Li Quanzheng^ORCID

Funder

National Institute on Aging

National Institutes of Health

National Heart Lung and Blood Institute

Publisher

Elsevier BV

Reference74 articles.

1. 2018 Robotic scene segmentation challenge;Allan,2020

2. The medical segmentation decathlon;Antonelli;Nature Commun.,2022

3. Polyp-SAM++: Can a text guided SAM perform better for polyp segmentation?;Biswas,2023

4. NCI-ISBI 2013 challenge: Automated segmentation of prostate structures;Bloch;Cancer Imaging Arch.,2015

5. On the opportunities and risks of foundation models;Bommasani,2021

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