Detection, grading and classification of coronary stenoses in computed tomography angiography

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6893 LNCS, Issue PART 3, 2011, Pages 25-32

  Kelm, B Michael ^a   Mittal, Sushil ^b,c   Zheng, Yefeng ^b   Tsymbal, Alexey ^a   Bernhardt, Dominik ^a   Vega Higuera, Fernando ^a   Zhou, S Kevin ^b   Meer, Peter ^c   Comaniciu, Dorin ^b  

^a SIEMENS AG   (Germany)

^b SIEMENS CORPORATE RESEARCH   (United States)

^c RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC DETECTION; AUTOMATIC SYSTEMS; CENTERLINE EXTRACTION; CENTERLINES; CLINICAL STUDY; COMPUTED TOMOGRAPHY ANGIOGRAPHY; CORONARY ARTERY DISEASE; PROCESSING TIME; STATE-OF-THE-ART PERFORMANCE; STENOSES; USER INVOLVEMENT;

ANGIOGRAPHY; CHEMICAL DETECTION; COMPUTERIZED TOMOGRAPHY; DISEASES; HEART; MEDICAL COMPUTING; MEDICAL IMAGING;

TOMOGRAPHY;

ALGORITHM; ANGIOCARDIOGRAPHY; ARTICLE; AUTOMATION; CLASSIFICATION; COMPUTER; COMPUTER ASSISTED TOMOGRAPHY; COMPUTER PROGRAM; CORONARY ARTERY OBSTRUCTION; HUMAN; IMAGE PROCESSING; METHODOLOGY; PATHOLOGY; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS; REPRODUCIBILITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; AUTOMATION; COMPUTERS; CORONARY ANGIOGRAPHY; CORONARY STENOSIS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; ROC CURVE; SOFTWARE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 80053521889     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23626-6_4     Document Type: Conference Paper

References (15)

1. Achenbach, S.: Cardiac CT: State of the art for the detection of coronary arterial stenosis. J. Cardiovasc. Comput. Tomogr. 1(1), 3-20 (2007)
2. Achenbach, S., Anders, K., Kalender,W.: Dual-source cardiac computed tomography: Image quality and dose considerations. Eur. Radiol. 18, 1188-1198 (2008)
3. Anders, K., Petit, I., Achenbach, S., Pflederer, T.: Diagnostic utility of automated stenosis detection in dual source CT coronary angiography as a stand alone or add-on tool. In: Proc. SCCT (2010)
4. Breiman, L.: Random forests. Mach. Learn. 45(1), 5-32 (2001)
5. Gallagher, M.J., Raff, G.L.: Use of multislice CT for the evaluation of emergency room patients with chest pain: the so-called "triple rule-out". Cath. and Cardiovasc. Interv. 71(1), 92-99 (2008)
6. Gülsün, M.A., Tek, H.: Robust vessel tree modeling. In:Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 602-611. Springer, Heidelberg (2008)
7. Halpern, E.J., Halpern, D.J.: Diagnosis of coronary stenosis with CT angiography comparison of automated computer diagnosis with expert readings. Acad. Radiol. 18, 324-333 (2011)
8. Lesage,D.,Angelini,E.D.,Bloch, I.,Funka-Lea,G.:Areviewof3Dvessel lumensegmentation techniques: Models, features and extraction schemes.Med. ImageAnal. 13(6), 819-845 (2009)
9. Li, K.,Wu, X., Chen, D.Z., Sonka,M.: Optimal surface segmentation in volumetric images-a graph-theoretic approach. IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 119-134 (2006)
10. Metz, C., Schaap,M., vanWalsum, T., van der Giessen, A.,Weustink, A.,Mollet, N., Krestin, G., Niessen, W.: 3D segmentation in the clinic: A grand challenge II - coronary artery tracking. In: MICCAI Workshop on 3D Segmentation in the Clinic: A Grand Challenge (2008)
11. Mittal, S., Zheng, Y., Georgescu, B., Vega-Higuera, F., Zhou, S., Meer, P., Comaniciu, D.: Fast automatic detection of calcified coronary lesions in 3D cardiac CT images. In: Proc. MICCAI Workshop on Machine Learning in Medical Imaging (2010)
12. Pugliese, F., Hunink, M.G.M., Gruszczynska, K., Alberghina, F., Malag, R., van Pelt, N., Mollet, N.R., Cademartiri, F., Weustink, A.C., Meijboom, W.B., Witteman, C.L.M., De Feyter, P.J., Krestin, G.P.: Learning Curve for Coronary CT Angiography: What Constitutes Sufficient Training? Radiol. 251(2), 359-368 (2009)
13. Rinck, D., Krüger, S., Reimann, A., Scheuering, M.: Shape-based segmentation and visualization techniques for evaluation of atherosclerotic plaques in coronary artery disease. In: Proc. SPIE Int. Soc. Opt. Eng., vol. 6141, pp. 61410G-9 (2006)
14. Teßmann, M., Vega-Higuera, F., Fritz, D.: Learning-based detection of stenotic lesions in coronary CT data. In: Proc. of Vision, Modeling, and Visualization, pp. 189-198 (2008)
15. Wesarg, S., Khan, M.F., Firle, E.: Localizing calcifications in cardiac CT data sets using a new vessel segmentation approach. J. of Dig. Imag. 19(3), 249-257 (2006)