Predicting Stenosis Severity and Localization in Coronary Artery using Deep Learning-Reference-Cited by-同舟云学术

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Predicting Stenosis Severity and Localization in Coronary Artery using Deep Learning

Published:2024-03-12 Issue: Volume:15 Page:117-125
ISSN:
Container-title:Proceedings of the 2024 7th International Conference on Machine Vision and Applications
language:
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Author:

Aono Masaki¹^ORCID,Asakawa Tetsuya¹^ORCID,Shinoda Hiroki¹^ORCID,Shimizu Kazuki²^ORCID,Togawa Takuya²^ORCID,Nomura Kei³^ORCID

Affiliation:

1. Computer Science and Engineering, Toyohashi University of Technology, Japan

2. Radiology, Toyohashi Heart Center, Japan

3. Brain, Toyohashi Heart Center, Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3653946.3653964

Reference18 articles.

1. TeraRecon Inc. [n. d.]. Aquarius iNtuition (AQi) Client Viewer. TeraRecon Inc. Durham NC USA. https://www.terarecon.com/aquarius-intuition-client-us-manual-4-4-13?locale=en

2. Feature Selection by ModifiedBoostARoota and Classification by CatBoost Model on High Dimensional Heart Disease Datasets

3. Predicting Stenosis in Coronary Arteries based on Deep Neural Network using Non-Contrast and Contrast Cardiac CT images

4. Deep learning prediction of quantitative coronary angiography values using myocardial perfusion images with a CZT camera

5. Deep learning-based end-to-end automated stenosis classification and localization on catheter coronary angiography

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