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Yuto Horima

As seen in: MDPI
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Articles by Yuto Horima

A Hessian-Based Deep Learning Preprocessing Method for Coronary Angiography Image Analysis

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By Yanjun Li, Takaaki Yoshimura, Yuto Horima, Hiroyuki Sugimori
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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A Preprocessing Method for Coronary Artery Stenosis Detection Based on Deep Learning

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By Yanjun Li, Takaaki Yoshimura, Hiroyuki Sugimori, Yuto Horima
| MDPI
1. Introduction Coronary heart disease, in which lifestyle and environmental factors are risk factors, is one of the leading cardiovascular diseases affecting the global population [1]. Coronary angiography has been used clinically for decades as the “gold standard” for the diagnosis of coronary heart disease [2]. Invasive coronary angiography (ICA) is an important method for arterial stenosis detection and is widely used in clinical treatment.
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