title: An image registration method for colposcopic images.
abstract: A nonrigid body image registration method for spatiotemporal alignment of image sequences obtained from colposcopy examinations to detect precancerous lesions of the cervix is proposed in this paper. The approach is based on time series calculation for those pixels in the first image of the sequence and a division of such image into small windows. A search process is then carried out to find the window with the highest affinity in each image of the sequence and replace it with the window in the reference image. The affinity value is based on polynomial approximation of the time series computed and the search is bounded by a search radius which defines the neighborhood of each window. The proposed approach is tested in ten 310-frame real cases in two experiments: the first one to determine the best values for the window size and the search radius and the second one to compare the best obtained results with respect to four registration methods found in the specialized literature. The obtained results show a robust and competitive performance of the proposed approach with a significant lower time with respect to the compared methods.
authors.affiliation: Department of Artificial Intelligence, University of Veracruz, Sebastián Camacho 5, 91000 Centro Xalapa, VER, Mexico.
authors.forename: Efrén
authors.initials: E
authors.lastname: Mezura-Montes
authors.forename: Héctor-Gabriel
authors.initials: HG
authors.lastname: Acosta-Mesa
authors.forename: Darío-del-Sinaí
authors.initials: DD
authors.lastname: Ramírez-Garcés
authors.forename: Nicandro
authors.initials: N
authors.lastname: Cruz-Ramírez
authors.forename: Rodolfo
authors.initials: R
authors.lastname: Hernández-Jiménez
mesh_terms: D003127:Colposcopy / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D011230:Precancerous Conditions / Q000175:diagnosis; D013997:Time Factors; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis