Diabetic foot ulcer segmentation using logistic regression, DBSCAN clustering and mathematical morphology operators
Heras-Tang, Armando (University of Havana)
Valdes-Santiago, Damian (University of Havana)
León-Mecías, Ángela Mireya (University of Havana)
Baguer Díaz-Romañach, Marta Lourdes (University of Havana)
Mesejo-Chiong, José Alejandro (University of Havana)

Date:	2022
Note:	Acknowledgements. We would like to thank the patients, volunteers, and co-workers of The Cuban National Institute of Angiology and Vascular Surgery (INACV, by its Spanish acronym), La Habana, Cuba, specially to Dr. Jose Ignacio Fernandez Montequín, Ph.D. The present study was reviewed and approved by the Ethics Committee of the INACV according to the ethical principles of the World Medical Association (Declaration of Helsinki). Written informed consent was obtained from all healthy volunteers (without diabetes) and from all people with DFU included in the study. This research was developed as part of the project "Development of methodologies and algorithms aimed at supporting the imaging diagnosis of diabetic foot ulcer" from the National Program of Health Determinants, Risks and Prevention of Diseases in Vulnerable Groups, Code 1901100, National Institute of Hygiene and Epidemiology, Ministry of Public Health, Cuba, 2019-2021.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Diabetic foot ulcer ; Supervised learning ; Image segmentation ; DFU
Published in:	ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 21 Núm. 2 (2022) , p. 22-39 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.cat/article/view/1413
DOI: 10.5565/rev/elcvia.1413

16 p, 2.4 MB

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