Computer aided diagnosis system using dermatoscopical image

López Labraca, Javier

Publication:
Computer aided diagnosis system using dermatoscopical image

dc.contributor.advisor	Díaz de María, Fernando
dc.contributor.author	López Labraca, Javier
dc.contributor.departamento	UC3M. Departamento de Teoría de la Señal y Comunicaciones	es
dc.date.accessioned	2018-04-16T14:24:11Z
dc.date.available	2018-04-16T14:24:11Z
dc.date.issued	2014
dc.date.submitted	2014-07-11
dc.description.abstract	Computer Aided Diagnosis (CAD) systems for melanoma detection aim to mirror the expert dermatologist decision when watching a dermoscopic or clinical image. Computer Vision techniques, which can be based on expert knowledge or not, are used to characterize the lesion image. This information is delivered to a machine learning algorithm, which gives a diagnosis suggestion as an output. This research is included into this field, and addresses the objective of implementing a complete CAD system using ‘state of the art’ descriptors and dermoscopy images as input. Some of them are based on expert knowledge and others are typical in a wide variety of problems. Images are initially transformed into oRGB, a perceptual color space, looking for both enhancing the information that images provide and giving human perception to machine algorithms. Feature selection is also performed to find features that really contribute to discriminate between benign and malignant pigmented skin lesions (PSL). The problem of robust model fitting versus statistically significant system evaluation is critical when working with small datasets, which is indeed the case. This topic is not generally considered in works related to PSLs. Consequently, a method that optimizes the compromise between these two goals is proposed, giving non-overfitted models and statistically significant measures of performance. In this manner, different systems can be compared in a fairer way. A database which enjoys wide international acceptance among dermatologists is used for the experiments.	es
dc.description.degree	Ingeniería de Sistemas Audiovisuales	es
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/10016/26651
dc.language.iso	eng	es
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España	*
dc.rights.accessRights	open access	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/	*
dc.subject.eciencia	Biología y Biomedicina	es
dc.subject.other	Biomarkers	es
dc.subject.other	Computer-aided diagnosis	es
dc.subject.other	Image processing	es
dc.subject.other	Melanoma analysis	es
dc.subject.other	Dermatologists	es
dc.title	Computer aided diagnosis system using dermatoscopical image	es
dc.type	bachelor thesis	*
dspace.entity.type	Publication