@InProceedings{ParolinHerzJung:2010:SeDiMe,
author = "Parolin, Alessandro and Herzer, Eduardo and Jung, Claudio R.",
affiliation = "Unisinos and Unisinos and UFRGS",
title = "Semi-Automated Diagnosis of Melanoma Through the Analysis of
Dermatological Images",
booktitle = "Proceedings...",
year = "2010",
editor = "Bellon, Olga and Esperan{\c{c}}a, Claudio",
organization = "Conference on Graphics, Patterns and Images, 23. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "image processing, medical imaging, classification, MDA-FKT.",
abstract = "Melanoma is the deadliest kind of skin cancer, but it can be 100%
cured if recognized early in advance. This paper proposes a
non-invasive automated skin lesion classifier based on digitized
dermatological images. In the proposed approach, the lesion is
initially segmented using snakes guided by an edge map based on
the Wavelet Transform (WT) computed at different resolutions. A
set of features is extracted from lesion pixels, and a
probabilistic classifier is used to identify melanoma lesions. The
detection rate of the proposed system can be adjusted to control
the tradeoff between false positives and false negatives, and
experimental results indicated that a false negative rate of 1.89%
can be achieved, in a total accuracy rate of 82.55%.",
conference-location = "Gramado, RS, Brazil",
conference-year = "30 Aug.-3 Sep. 2010",
doi = "10.1109/SIBGRAPI.2010.18",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2010.18",
language = "en",
ibi = "8JMKD3MGPBW34M/387LT3L",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/387LT3L",
targetfile = "sib10_dermato_camera_ready.pdf",
urlaccessdate = "2024, May 03"
}