Greedy algorithm for error correction in automatically produced boundaries from low contrast ventriculograms

Pattern Analysis and Applications

Volumn 3, Issue 1, 2000, Pages 39-60

  Suri, J S ^a,c   Haralick, R M ^a   Sheehan, F H ^b  

^a University of Washington   (United States)

^b UNIVERSITY OF WASHINGTON MEDICAL CENTER   (United States)

^c Division Ot Image Guided Surgery   (United States)

Author keywords

Boundaries; Calibration; Left ventricle; Low contrast; Motion; Optimisation; Polyline

Indexed keywords

EID: 0034421371     PISSN: 14337541     EISSN: None     Source Type: Journal    
DOI: 10.1007/s100440050005     Document Type: Article

References (31)

1. Lee CK. Automated Boundary Tracing Using Temporal Information. PhD Thesis, Department of Electrical Engineering, University of Washington, Seattle, 1994
2. Moore RJ. Imaging Principles of Cardiac Angiography. Aspen, Rockville, MD, pp 1-258
3. Moodi DS, Yiannikas J. Digital Subtraction Angiography of the heart and lungs. Grune and Stratton (Harcourt Brace Jovanovich), New York, NY, 1986
4. Mancini GBJ. Clinical Applications of Cardiac Digital Angiography. Raven Press, NY, 1988, pp 1-324.
5. Chow CK, Kaneko T. Border detection based on local characteristics. Computers in Biomedicine Research 1972; 5:388-410
6. Griffith RL, Grant C, Kaufman H. An algorithm for locating the aortic valve and the apex in left ventricular angiocardiograms. IEEE Transactions on Biomedical Engineering 1974; 21(5): 345-349
7. Tanaka et al. U.S. Patent #: 4,952,805, Method of judging the presence or absence of a limited irradiation field, method of selecting a correct irradiation field, and method of judging correctness or incorrectness of an irradiation field, 1990
8. De Jong LP, Slager CJ. Detection of the left ventricle outline in angiographs using TV signal processing technique. IEEE Transactions in Biomedical Engineering 1975; 22(3):230-237
9. Reiber JHC. US Patent #: 4,101,961, Contour Detector and Data Acquisition System for the left ventricular outline, July 18 1978
10. Han CY, Porembka DT, Kwun-Nan. US Patent #: 5,457,754, Method for Automatic contour extraction of a cardiac image, October 10 1995
11. Wollschleger H, Tenspiel RW, Solzbach U, Zeiher AM, Just H. Reliable automatic frame-by-frame contour detection of digitised LV cine-angiograms. IEEE Computers in Cardiology 1988; 353-356
12. Van Bree. Improving left ventricular border recognition using probability surfaces. IEEE Computers in Cardiology 1989; 121-124
13. Kass, Wikins, Terzapolous. Snakes: active contour models. Int J Computer Vision 1988; 1(4):321-331
14. Cootes TF, Taylor CJ, Cooper DH, Graham J. Active shape models: their training and applications. Computer Vision and Image Understanding 1995; 61(1):38-59
15. Chiou GI, Hwang J-N. A neural network based stochastic active contour model (NNS-SNAKE) for contour finding of distinct features. IEEE Trans Image Proc 1985; 4(10):1407
16. Duncan J, Owen R, Anandan P, Staib L, et al. Shape-based tracking of left ventricle wall motion. Information Processing in Medical Imaging 1991; 41-44
17. Duncan JS, Owen RL, Staib LH, Anandan P. Measurement of non-rigid motion using contour shape descriptors. IEEE Trans. Pattern Recognition and Machine Intelligence (PAMI) 1991; 5:318-330
18. Suri JS, Haralick RM, Sheehan FH. Accurate left ventricle apex position and boundary estimation from noisy ventriculograms. Proc. IEEE Computers in Cardiology, Indianapolis, 1996
19. Suri JS, Haralick RM, Sheehan FH. Left ventricle longitudinal axis fitting and LV apex estimation using a robust algorithm and its performance: a parametric apex model. Proc International Conference in Image Processing, Santa Barbara, CA, 1997
20. Suri JS, Haralick RM, Sheehan FH. Two automatic calibration algorithms for left ventricle boundary estimation in X-ray images. Proc IEEE Int Conf of Engineering in Medicine and Biology (EMBS), Amsterdam, The Netherlands, October 31-November 3 1996
21. Suri JS, Haralick RM, Sheehan FM. Two automatic training-based forced calibration algorithms for left ventricle boundary estimation in cardiac images. 19th International Conference of IEEE Engineering in Medicine and Biology (EMBS), Chicago, IL, October 30-November 2 1997, pp 528-532
22. Klausner SC, Blair TJ, Bulawa WF, Jeppson GM, Jensen RL, Clayton PD. Quantitative analysis of segmental wall motion throughout systole and diastole in the normal human left ventricle. Circulation 1982; 65(3):580-590
23. Bolson EL, Kilman S, Sheehan FH, Dodge HT. Left ventricular segmental wall motion - a new method using local direction information. IEEE Computers in Cardiology 1980; 245
24. Sheehan FH, Stewart DK, Dodge HT et al. Variability in the measurement of regional left ventricular wall motion from contrast angiograms. Circulation 1983; 68(3):550-559
25. Press WH, Flannery BP, Teukolsky SA, Vetterling WT. Numerical Recipes in C. Cambridge University Press, Cambridge, 1988
26. Haralick RM, Shapiro LG. Computer and Robot Vision. Cambridge, Addison-Wesley, Reading, MA, 1991
27. Chen T, Lin WC, Chen CT. Artificial Neural Networks for 3-d nonrigid motion analysis. Artificial Neural Networks in Engineering, St. Louis, Ml, November 1992
28. Beier J, Joerke T, Lempert S, Wellnhofer E, Oswald H, Fleck E. A comparison of 7 different volumetry methods of left and right ventricle using post-mortem phantoms. IEEE Computers in Cardiology 1993; 33-36
29. Geman D, Geman S, Graffigne C, Dong P. Boundary detection by constrained optimisation. IEEE Pattern Recognition and Machine Intelligence 1990; 12:609-628
30. Anthony HM, Cox MG. An automatic algorithm for immunoassay curve calibration using controlled quadratic splines. IMA Journal of Mathematics Applied in Medicine and Biology 1989; 6(2):91-110
31. Chen CW, Huang TS. Modeling, analysis, and visualisation of left ventricle shape and motion by hierarchical decomposition. IEEE Trans on Pattern Analysis and Machine Intelligence 1994; 16(4):342-356