An Enhanced Convolutional Neural Network Based on L1 Regularization for Segmentation of Coronary Arteries in X-Ray Angiograms-Reference-Cited by-同舟云学术

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An Enhanced Convolutional Neural Network Based on L1 Regularization for Segmentation of Coronary Arteries in X-Ray Angiograms

Published:2024-02-19 Issue: Volume:7 Page:1-8
ISSN:
Container-title:2024 5th International Conference on Advancements in Computational Sciences (ICACS)
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Author:

Wahid Fazli¹,Ma Yingliang¹,Sheikh Ramla²,Aamir Muhammad³

Affiliation:

1. University of East Anglia,School of Computing Sciences,Norwich,United Kingdom

2. University of Haripur,Department of Information Technology,Khyber Pakhtunkhwa,Pakistan

3. University of Derby,Data Science Research Centre Colloge of Science and Engineering,Derby,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10473181/10473230/10473261.pdf?arnumber=10473261

Reference26 articles.

1. Towards automated coronary artery segmentation: A systematic review

2. Automated segmentation of normal and diseased coronary arteries – The ASOCA challenge

3. A systematic review and meta-analysis of multidetector computed tomography in the assessment of coronary artery bypass grafts

4. Automatic Segmentation of Coronary Arteries in X-ray Angiograms using Multiscale Analysis and Artificial Neural Networks

5. Automatic extraction of coronary artery tree on coronary angiograms by morphological operators

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