Automated Detection and Diameter Estimation for Mouse Mesenteric Artery Using Semantic Segmentation | Zendy

Akinori Higaki | Zendy; Ahmad Mahmoud | Zendy; Pierre Paradis | Zendy; Ernesto L. Schiffrin | Zendy

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Automated Detection and Diameter Estimation for Mouse Mesenteric Artery Using Semantic Segmentation

Author(s) -

Akinori Higaki,

Ahmad Mahmoud,

Pierre Paradis,

Ernesto L. Schiffrin

Publication year - 2021

Publication title -

journal of vascular research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.58

H-Index - 74

eISSN - 1423-0135

pISSN - 1018-1172

DOI - 10.1159/000516842

Subject(s) - lumen (anatomy) , segmentation , superior mesenteric artery , nuclear medicine , medicine , mathematics , computer science , artificial intelligence

Pressurized myography is useful for the assessment of small artery structures and function. However, this procedure requires technical expertise for sample preparation and effort to choose an appropriate sized artery. In this study, we developed an automatic artery/vein differentiation and a size measurement system utilizing machine learning algorithms.

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