Finding similar 2D X-ray coronary angiograms

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

Volumn 7512 LNCS, Issue , 2012, Pages 501-508

  Syeda Mahmood, Tanveer ^a   Wang, Fei ^a   Kumar, R ^a   Beymer, D ^a   Zhang, Y ^a   Lundstrom, Robert ^b   McNulty, Edward ^b  

^a IBM ALMADEN RESEARCH CENTER   (United States)

^b Kaiser San Francisco Medical Center   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MEDICAL COMPUTING; MEDICAL IMAGING;

CLINICAL HISTORY; CLINICAL PRACTICES; CORONARY ARTERIES; VISUAL FEATURE;

HEART;

ALGORITHM; ANGIOCARDIOGRAPHY; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; CORONARY ARTERY DISEASE; HUMAN; IMAGE QUALITY; IMAGE SUBTRACTION; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; CORONARY ANGIOGRAPHY; CORONARY ARTERY DISEASE; HUMANS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

MLCS; MLOWN;

EID: 84872930652     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33454-2_62     Document Type: Conference Paper

References (15)

1. Chalopin, C., Finet, G., Magnin, I.E.: Modeling the 3D coronary tree for labeling purposes. Medical Image Analysis 5(4), 301–315 (2001)
2. Chen, T., Funka-Lea, G., Comaniciu, D.: Robust and Fast Contrast Inflow Detection for 2D X-ray Fluoroscopy. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part I. LNCS, vol. 6891, pp. 243–250. Springer, Heidelberg (2011)
3. Dehkordi, M.T., Sadri, S., Doosthoseini, A.: A review of coronary vessel segmentation algorithms. Journal of Medical Signals and Sensors 1(1) (2011)
4. Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale Vessel Enhancement Filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MIC-CAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)
5. Hsu, J.T.: Impact of calcification length ratio on the intervention for chronic total occlusions. Intl. Jl. of Cardiology, 135–141 (2011)
6. Kumar, R., Reina, A.V., Pfister, H.: Radon-like features and their application to connectomics. In: IEEE Workshop MMBIA (2010)
7. Lara, S., et al.: A semi-automatic method for segmentation of the coronary artery tree from angiography. In: ACM Symposium on Graphics, vol. 27(3), pp. 236–239 (2009)
8. Otsu, N.: A threshold selection method from gray-scale histogram. IEEE Trans. Syst., Man, Cybern. 9(1), 62–66 (1979)
9. Russell, B.C., et al.: LabelMe: a database and web-based tool for image annotation. International Journal of Computer Vision, 157–173 (2008)
10. Sato, Y., et al.: Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. In: Medical Image Analysis, pp. 143–168 (1998)
11. Shental, N., Hertz, T., Weinshall, D., Pavel, M.: Adjustment Learning and Relevant Component Analysis. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part IV. LNCS, vol. 2353, pp. 776–790. Springer, Heidelberg (2002)
12. Sianos, G., et al.: The syntax score: and angiographic tool grading the complexity of coronary artery disease. EuroIntervention, 219–227 (2005)
13. Syeda-Mahmood, T., et al.: Automatic selection of keyframes from angiogram videos. In: ICPR (2010)
14. Zhang, T.Y., Suen, C.: A fast parallel algorithm for thinning digital patterns. Communications of ACM 27(3), 236–239 (1984)
15. Zhao, F., Bhotika, R.: Coronary artery tree tracking with robust junction detection in 3D CT angiography. In: ISBI, pp. 2066–2071 (2011)