A Fully Automatic based Deep Learning Approach for Aneurysm Detection in DSA Images-Reference-Cited by-同舟云学术

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A Fully Automatic based Deep Learning Approach for Aneurysm Detection in DSA Images

Published:2018-12 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS)
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Author:

Rahmany Ines,Guetari Ramzi,Khlifa Nawres

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8703641/8708850/08708897.pdf?arnumber=8708897

Cited by 10 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. Nested Contrastive Boundary Learning: Point Transformer Self-Attention Regularization for 3D Intracranial Aneurysm Segmentation;Technologies;2024-02-21

2. Automatic Detection of AMD and DME Retinal Pathologies Using Deep Learning;International Journal of Biomedical Imaging;2023-11-24

3. FSTIF-UNet: A Deep Learning-Based Method Towards Automatic Segmentation of Intracranial Aneurysms in Un-Reconstructed 3D-RA;IEEE Journal of Biomedical and Health Informatics;2023-08

4. Towards quantitative digital subtraction perfusion angiography: An animal study;Medical Physics;2023-05-24

5. A Tool for Thermal Image Annotation and Automatic Temperature Extraction around Orthopedic Pin Sites;2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS);2022-12-05

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