Computer aided diagnosis system using dermatoscopical image

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dc.contributor.advisor Díaz de María, Fernando
dc.contributor.author López Labraca, Javier
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.identifier.uri http://hdl.handle.net/10016/26651
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.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Biomarkers
dc.subject.other Computer-aided diagnosis
dc.subject.other Image processing
dc.subject.other Melanoma analysis
dc.subject.other Dermatologists
dc.title Computer aided diagnosis system using dermatoscopical image
dc.type bachelorThesis
dc.subject.eciencia Biología y Biomedicina
dc.rights.accessRights openAccess
dc.description.degree Ingeniería de Sistemas Audiovisuales
dc.contributor.departamento Universidad Carlos III de Madrid. Departamento de Teoría de la Señal y Comunicaciones
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