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Katouzian, A.* ; Karamalis, A.* ; Lisauskas, J.* ; Eslami, A. ; Navab, N.*

IVUS-histology image registration.

Lect. Notes Comput. Sc. 7359, 141-149 (2012)
DOI
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
In this paper, for the first time, we present a systematic framework to register intravascular ultrasound (IVUS) images with histology correspondences. We deployed intermediate representations of images, generating segmentation masks corresponding to lumen and media-adventitia borders for both histology and IVUS images, incorporated into a non-rigid registration framework using discrete multi-labeling and approximate curvature penalty for smoothness regularization. The resulting deformation field was then applied to the original histology image to transfer it to IVUS coordinate system. Finally, the results were quantified on 14 cross sections of interest. The main contribution of this work is that the registered results could be used for systematic labeling of tissues, which ultimately will lead to reliable construction of training dataset for feature extraction and supervised classification of atherosclerotic tissues.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Atherosclerosis; Histology; Intravascular Ultrasound (IVUS); Registration
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
Zeitschrift Lecture Notes in Computer Science
Quellenangaben Band: 7359, Heft: , Seiten: 141-149 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]
Institut(e) Institute of Computational Biology (ICB)