Spectral features selection and classification for bimodal optical spectroscopy applied to bladder cancer in vivo diagnosis.

Date publication

janvier 2014

Auteurs

Membres identifiés du Cancéropôle Est :
Dr LEROUX Agnès

Tous les auteurs :
Pery E, Blondel WC, Tindel S, Ghribi M, Leroux A, Guillemin F

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/21216703

Résumé

This paper describes an experimental study combining spatially resolved autofluorescence (AF) and diffuse reflectance (DR) fibred spectroscopies to discriminate in vivo between healthy and pathological tissues in a preclinical model of bladder cancer. Then, a detailed step-by-step analysis scheme is presented for the extraction and the selection of discriminative spectral features (correlation, linear discriminant, and logistic regression analysis), and for the spectroscopic data final classification algorithms (regularized discriminant analysis and support vector machines). Significant differences between healthy, inflammatory, and tumoral tissues were obtained by selecting a reasonable number of discriminant spectral features from AF, DR, and intrinsic fluorescence spectra, leading to improved sensitivity (87%) and specificity (77%) compared to monomodality (AF or DR alone).

Référence

IEEE Trans Biomed Eng. 2014 Jan;61(1):207-16