Multimodal Self-Supervised Learning for Lesion Localization-Reference-Cited by-同舟云学术

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Multimodal Self-Supervised Learning for Lesion Localization

Published:2024-05-27 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
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Author:

Yang Hao¹,Zhou Hong-Yu²,Li Cheng¹,Huang Weijian¹,Liu Jiarun¹,Liang Yong³,Shi Guangming³,Zheng Hairong¹,Liu Qiegen⁴,Wang Shanshan¹

Affiliation:

1. Chinese Academy of Sciences,Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology,Shenzhen,China

2. The University of Hong Kong,Department of Computer Science,Pokfulam,China

3. Peng Cheng Laboratory,Shenzhen,China

4. Nanchang University,Department of Electronic Information Engineering,China

Funder

National Natural Science Foundation of China

Peng Cheng Laboratory

Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635268.pdf?arnumber=10635268

Reference16 articles.

1. Automated deep-neural-network surveillance of cranial images for acute neurologic events

2. Annotation-efficient deep learning for automatic medical image segmentation

3. Enhancing representation in radiography-reports foundation model: a granular alignment algorithm using masked contrastive learning

4. A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics

5. A Unified Visual Information Preservation Framework for Self-supervised Pre-training in Medical Image Analysis

Cited by 2 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. Enhancing the vision–language foundation model with key semantic knowledge-emphasized report refinement;Medical Image Analysis;2024-10

2. Enhancing representation in radiography-reports foundation model: a granular alignment algorithm using masked contrastive learning;Nature Communications;2024-09-02

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