Coronary motion estimation from CTA using probability atlas and diffeomorphic registration

Dong Ping Zhang, Laurent Risser, François Xavier Vialard, Philip Edwards, Coert Metz, Lisan Neefjes, Nico Mollet, Wiro Niessen, Daniel Rueckert

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

2 Scopus citations

Abstract

In this paper, we present a method for coronary artery motion estimation from 4D cardiac CT angiogram (CTA) data sets. The proposed method potentially allows the construction of patient-specific 4D coronary motion model from pre-operative CTA which can be used for guiding totally endoscopic coronary artery bypass surgery (TECAB). The proposed approach consists of three steps: Firstly, prior to motion tracking, we form a coronary probability atlas from manual segmentations of the CTA scans of a number of subjects. Secondly, the vesselness response image is calculated and enhanced for end-diastolic and end-systolic CTA images in each 4D sequence. Thirdly, we design a special purpose registration framework for tracking the highly localized coronary motion. It combines the coronary probability atlas, the intensity information from the CTA image and the corresponding vesselness response image to fully automate the coronary motion tracking procedure and improve its accuracy. We performed pairwise 3D registration of cardiac time frames by using a multi-channel implementation of the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework, where each channel contains a given level of description of the registered shapes. For validation, we compare the automatically tracked coronaries with those segmented manually at end-diastolic phase for each subject.

Original languageEnglish
Title of host publicationMedical Imaging and Augmented Reality - 5th International Workshop, MIAR 2010, Proceedings
Pages78-87
Number of pages10
DOIs
StatePublished - 2010
Externally publishedYes
Event5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010 - Beijing, China
Duration: 19 Sep 201020 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6326 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010
Country/TerritoryChina
CityBeijing
Period19/09/1020/09/10

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