How Segment Anything Model (Sam) Boost Medical Image Segmentation: A Survey-Reference-Cited by-同舟云学术

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How Segment Anything Model (Sam) Boost Medical Image Segmentation: A Survey

Published:2023 Issue: Volume: Page:
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Author:

Zhang Yichi,Jiao Rushi

Publisher

Elsevier BV

Reference45 articles.

1. A survey on deep learning in medical image analysis;G Litjens;Medical image analysis,2017

2. Abdomenct-1k: Is abdominal organ segmentation a solved problem?;J Ma;IEEE Transactions on Pattern Analysis and Machine Intelligence,2022

3. Large-scale multi-modal pre-trained models: A comprehensive survey;X Wang;Machine Intelligence Research,2023

Cited by 35 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. SAM-IE: SAM-based image enhancement for facilitating medical image diagnosis with segmentation foundation model;Expert Systems with Applications;2024-09

2. BubSAM: Bubble segmentation and shape reconstruction based on Segment Anything Model of bubbly flow;AIChE Journal;2024-08-21

3. Artificial Intelligence in Pancreatic Image Analysis: A Review;Sensors;2024-07-22

4. G-SAM: GMM-based segment anything model for medical image classification and segmentation;Cluster Computing;2024-07-17

5. Towards Training-Free Open-World Segmentation via Image Prompt Foundation Models;International Journal of Computer Vision;2024-07-16

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