Literature DB >> 20095269

Coronary centerline extraction from CT coronary angiography images using a minimum cost path approach.

C T Metz1, M Schaap, A C Weustink, N R Mollet, T van Walsum, W J Niessen.   

Abstract

PURPOSE: The application and large-scale evaluation of minimum cost path approaches for coronary centerline extraction from computed tomography coronary angiography (CTCA) data and the development and evaluation of a novel method to reduce the user-interaction time.
METHODS: A semiautomatic method based on a minimum cost path approach is evaluated for two different cost functions. The first cost function is based on a frequently used vesselness measure and intensity information, and the second is a recently proposed cost function based on region statistics. User interaction is minimized to one or two mouse clicks distally in the coronary artery. The starting point for the minimum cost path search is automatically determined using a newly developed method that finds a point in the center of the aorta in one of the axial slices. This step ensures that all computationally expensive parts of the algorithm can be precomputed.
RESULTS: The performance of the aorta localization procedure was demonstrated by a success rate of 100% in 75 images. The success rate and accuracy of centerline extraction was quantitatively evaluated on 48 coronary arteries in 12 images by comparing extracted centerlines with a manually annotated reference standard. The method was able to extract 88% and 47% of the vessel center-lines correctly using the vesselness/intensity and region statistics cost function, respectively. For only the proximal part of the vessels these values were 97% and 86%, respectively. Accuracy of centerline extraction, defined as the average distance from correctly automatically extracted parts of the centerline to the reference standard, was 0.64 mm for the vesselness/intensity and 0.51 mm for the region statistics cost function. The interobserver variability was 99% for the success rate measure and 0.42 mm for the accuracy measure. Qualitative evaluation using the best performing cost function resulted in successful centerline extraction for 233 out of the 252 coronaries (92%) in 63 additional CTCA images.
CONCLUSIONS: The presented results, in combination with minimal user interaction and low computation time, show that minimum cost path approaches can effectively be applied as a preprocessing step for subsequent analysis in clinical practice and biomedical research.

Entities:  

Mesh:

Year:  2009        PMID: 20095269     DOI: 10.1118/1.3254077

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  12 in total

1.  Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography.

Authors:  Guanyu Yang; Pieter Kitslaar; Michel Frenay; Alexander Broersen; Mark J Boogers; Jeroen J Bax; Johan H C Reiber; Jouke Dijkstra
Journal:  Int J Cardiovasc Imaging       Date:  2011-06-03       Impact factor: 2.357

2.  Automatic segmentation, detection and quantification of coronary artery stenoses on CTA.

Authors:  Rahil Shahzad; Hortense Kirişli; Coert Metz; Hui Tang; Michiel Schaap; Lucas van Vliet; Wiro Niessen; Theo van Walsum
Journal:  Int J Cardiovasc Imaging       Date:  2013-08-08       Impact factor: 2.357

3.  Image Annotation by Eye Tracking: Accuracy and Precision of Centerlines of Obstructed Small-Bowel Segments Placed Using Eye Trackers.

Authors:  Alfredo Lucas; Kang Wang; Cynthia Santillan; Albert Hsiao; Claude B Sirlin; Paul M Murphy
Journal:  J Digit Imaging       Date:  2019-10       Impact factor: 4.056

4.  Comprehensive visualization of multimodal cardiac imaging data for assessment of coronary artery disease: first clinical results of the SMARTVis tool.

Authors:  Hortense A Kirişli; V Gupta; S W Kirschbaum; A Rossi; C T Metz; M Schaap; R J van Geuns; N Mollet; B P F Lelieveldt; J H C Reiber; T van Walsum; W J Niessen
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-09-24       Impact factor: 2.924

5.  Computerized analysis of coronary artery disease: performance evaluation of segmentation and tracking of coronary arteries in CT angiograms.

Authors:  Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Jean Kuriakose; Prachi Agarwal; Ella A Kazerooni; Lubomir M Hadjiiski; Smita Patel; Jun Wei
Journal:  Med Phys       Date:  2014-08       Impact factor: 4.071

6.  Automatic detection of aorto-femoral vessel trajectory from whole-body computed tomography angiography data sets.

Authors:  Xinpei Gao; Pieter H Kitslaar; Ricardo P J Budde; Shengxian Tu; Michiel A de Graaf; Liang Xu; Bo Xu; Arthur J H A Scholte; Jouke Dijkstra; Johan H C Reiber
Journal:  Int J Cardiovasc Imaging       Date:  2016-05-21       Impact factor: 2.357

7.  Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations.

Authors:  Guanglei Xiong; Peng Sun; Haoyin Zhou; Seongmin Ha; Briain O Hartaigh; Quynh A Truong; James K Min
Journal:  IEEE Trans Vis Comput Graph       Date:  2016-02-05       Impact factor: 4.579

8.  Development of a quantitative intracranial vascular features extraction tool on 3D MRA using semiautomated open-curve active contour vessel tracing.

Authors:  Li Chen; Mahmud Mossa-Basha; Niranjan Balu; Gador Canton; Jie Sun; Kristi Pimentel; Thomas S Hatsukami; Jenq-Neng Hwang; Chun Yuan
Journal:  Magn Reson Med       Date:  2017-10-17       Impact factor: 4.668

9.  Automated coronary artery tree extraction in coronary CT angiography using a multiscale enhancement and dynamic balloon tracking (MSCAR-DBT) method.

Authors:  Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Smita Patel; Lubomir M Hadjiiski; Jun Wei; Ella A Kazerooni
Journal:  Comput Med Imaging Graph       Date:  2011-05-20       Impact factor: 4.790

10.  Coronary arteries segmentation based on the 3D discrete wavelet transform and 3D neutrosophic transform.

Authors:  Shuo-Tsung Chen; Tzung-Dau Wang; Wen-Jeng Lee; Tsai-Wei Huang; Pei-Kai Hung; Cheng-Yu Wei; Chung-Ming Chen; Woon-Man Kung
Journal:  Biomed Res Int       Date:  2015-01-14       Impact factor: 3.411

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