Blood Vessel Segmentation from Low-Contrast and Wide-Field Optical Microscopic Images of Cranial Window by Attention-Gate-Based Network-Reference-Cited by-同舟云学术

Blood Vessel Segmentation from Low-Contrast and Wide-Field Optical Microscopic Images of Cranial Window by Attention-Gate-Based Network

Published:2022-06 Issue: Volume: Page:
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Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Author:

Wu Yunheng¹,Oda Masahiro¹,Hayashi Yuichiro¹,Takebe Takanori²,Nagata Shogo³,Wang Cheng¹,Mori Kensaku¹

Affiliation:

1. Nagoya University,Japan

2. Tokyo Medical and Dental University (TMDU),Japan

3. Keio University,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9856930/9856648/09857100.pdf?arnumber=9857100

Reference36 articles.

1. Vascular structure segmentation in stereomicroscope image;wu;The 40th the Japanese Society of Medical Imaging Technology Annual Meeting 2021,2021

2. Investigation on blood vessels segmentation from images of mouse’s cranial window based on deep learning;wu;IEICE Tech Rep MI2021-84,2021

3. Retina blood vessel segmentation using a U-Net based Convolutional Nneural Network;wang;Procedia Computer Science International Conference on Data Science (ICDS 2018),2018

4. Hierarchical retinal blood vessel segmentation based on feature and ensemble learning

5. Contrast Limited Adaptive Histogram Equalization

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