Authors:
Luís Rosado
and
Maria Vasconcelos
Affiliation:
Fraunhofer Portugal AICOS, Portugal
Keyword(s):
Mobile Devices, Segmentation, Teledermatology.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Design and Development Methodologies for Healthcare IT
;
Distributed and Mobile Software Systems
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Mobile Technologies
;
Mobile Technologies for Healthcare Applications
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Software Engineering
;
Telemedicine
Abstract:
Nowadays, skin cancer is considered one of the most common malignancies in the Caucasian population, thus
it is crucial to develop methodologies to prevent it. Because of that, Mobile Teledermatology (MT) is thriving,
allowing patients to adopt an active role in their health status while facilitating doctors to early diagnose skin
cancers. Skin lesion segmentation is one of the most important and difficult task in computerized image
analysis process, and so far the attention is mainly turned to dermoscopic images. In order to turn MT more
accurate, it is therefore fundamental to develop simple segmentation methodologies specifically designed for
macroscopic images or images acquired via smartphones, which is the main focus of this work. The proposed
method was applied in 80 images acquired via smartphones and promising results have been achieved: a mean
Jaccard index of 81%, mean True Detection Rate of 96% and mean Accuracy around 98%. The major goal of
this work is to develop a mobi
le application easily accessible for the general population, with the aim of raise
awareness and help both patients and doctors in the early diagnosis of skin cancers.
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