Institute of Information Theory and Automation

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Conference Paper (international conference)

Cervical cancer detection using colposcopic images: a temporal approach

Acosta-Mesa H. G., Zitová Barbara, Ríos-Figueroa H. V., Cruz-Ramírez N. V., Marín-Hernández A., Hernández-Jiménez R., Cocotle-Ronzón B. E., Hernández-Galicia E.

: Proceedings of the Mexican International Conference on Computer Science ENC'05, p. 1-7

: Mexican International Conference in Computer Science. ENC'05, (Puebla, MX, 26.09.2005-30.09.2005)

: CEZ:AV0Z10750506

: cervical cancer detection, colposcopy, digital image processing, time analysis

(eng): Methodology for analysis of the colposcopic images is presented to help experts to create robust diagnosis of cervical cancer. The image registration was applied using phase correlation followed by a locally applied algorithm based on the normalized cross correlation. Time analysis of the obtained features is realized in the Hough space. Supervised Bayesian learning is used for classification and resulting labels are used for tissue categorization.

(cze): V nasem clanku je prezentovana metodologie pro analyzu kolposkopickych obrazku, ktera muze napomoci expertum vytvorit kvalitnejsi diagnozu rakoviny cipku. Geometricka registrace snimku je realizovana pomoci fazove korelace, nasledovane lokalne aplikovanou normalizovanou kros-korelaci. Casova analyza ziskanych priznaku je provedena v Hough prostoru. Zaverecna klasifikace tkani vychazi z teorie Bayesovske klasifikace.

: 09K

: JD

2019-01-07 08:39