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dc.contributorVilaseca Ricart, Meritxell
dc.contributorDelpueyo Español, Xana
dc.contributor.authorLiang, Chenxue
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Òptica i Optometria
dc.descriptionEn col·laboració amb la Universitat Autònoma de Barcelona (UAB) i la Universitat de Barcelona (UB).
dc.description.abstractSkin cancer is the most prevalent form of cancer, and melanoma is one of the most threat disease of it. But it can be cured if it is detected early enough. Multispectral imaging is a potential method to differenciate melanoma from nevi as it provides spectral images with information of absorbance and reflectance. With this aim, spectral images along the visible and near infrared range (from 415nm to 995nm) of 165 lesions including nevi, melanomas and basal cell carcinomas were processed in this master thesis. After obtaining all data in terms of reflectance and absorbance and other related parameters for each pixel of the segmented lesions, a statistical analysis was carried out to quantify their spatial distribution all over each lesion. Algorithms such as Support vector machine (SVM) and Discriminant Analysis (DA) were used as a means of classifying the lesions. The results show that DA linear classifier provides a better diagnosis than the SVM. BCCs are easier to discriminate from nevi than melanomas.
dc.publisherUniversitat Politècnica de Catalunya
dc.rightsS'autoritza la difusió de l'obra mitjançant la llicència Creative Commons o similar 'Reconeixement-NoComercial- SenseObraDerivada'
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshImage processing -- Digital techniques
dc.subject.otherskin cancer
dc.subject.othermultispectral imaging system
dc.titleMultispectral imaging methods for the diagnosis of skin cancer lesions
dc.typeMaster thesis
dc.subject.lemacImatges -- Processament -- Tècniques digitals
dc.subject.lemacPell -- Càncer
dc.rights.accessOpen Access
dc.audience.mediatorEscola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona

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