IVUS-histology image registration

Amin Katouzian, Athanasios Karamalis, Jennifer Lisauskas, Abouzar Eslami, Nassir Navab

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationBiomedical Image Registration - 5th International Workshop, WBIR 2012, Proceedings
Pages141-149
Number of pages9
DOIs
StatePublished - 2012
Event5th International Workshop on Biomedical Image Registration, WBIR 2012 - Nashville, TN, United States
Duration: 7 Jul 20128 Jul 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7359 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Workshop on Biomedical Image Registration, WBIR 2012
Country/TerritoryUnited States
CityNashville, TN
Period7/07/128/07/12

Keywords

  • Atherosclerosis
  • Histology
  • Intravascular Ultrasound (IVUS)
  • Registration

Fingerprint

Dive into the research topics of 'IVUS-histology image registration'. Together they form a unique fingerprint.

Cite this