Dermoscopy Image Analysis: Overview and Future Directions.


Journal

IEEE journal of biomedical and health informatics
ISSN: 2168-2208
Titre abrégé: IEEE J Biomed Health Inform
Pays: United States
ID NLM: 101604520

Informations de publication

Date de publication:
03 2019
Historique:
pubmed: 1 2 2019
medline: 31 12 2019
entrez: 1 2 2019
Statut: ppublish

Résumé

Dermoscopy is a non-invasive skin imaging technique that permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. While studies on the automated analysis of dermoscopy images date back to the late 1990s, because of various factors (lack of publicly available datasets, open-source software, computational power, etc.), the field progressed rather slowly in its first two decades. With the release of a large public dataset by the International Skin Imaging Collaboration in 2016, development of open-source software for convolutional neural networks, and the availability of inexpensive graphics processing units, dermoscopy image analysis has recently become a very active research field. In this paper, we present a brief overview of this exciting subfield of medical image analysis, primarily focusing on three aspects of it, namely, segmentation, feature extraction, and classification. We then provide future directions for researchers.

Identifiants

pubmed: 30703051
doi: 10.1109/JBHI.2019.2895803
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

474-478

Auteurs

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Classifications MeSH