A novel segmentation method using multiresolution analysis with 3D visualization for X-ray coronary angiogram images

Journal of Medical Engineering and Technology

Volumn 32, Issue 3, 2008, Pages 235-244

  Nirmaladevi, S ^a   Lavanya, P ^a   Kumaravel, N ^a  

^a ANNA UNIVERSITY   (India)

Author keywords

3D visualization; Angiogram; Entropy; Multiresolution analysis; Multithresholding

Indexed keywords

ANGIOGRAPHY; BLOOD VESSELS; DATA VISUALIZATION; MEDICAL IMAGING; MULTIRESOLUTION ANALYSIS; MUSCLE;

ANGIOGRAPHIC IMAGES; MULTITHRESHOLDING; PERFORMANCE ANALYSIS;

IMAGE SEGMENTATION;

ALGORITHM; ANGIOCARDIOGRAPHY; ARTICLE; AUTOMATION; CORRELATION COEFFICIENT; DIAGNOSTIC ACCURACY; DISEASE SEVERITY; IMAGE QUALITY; PROBABILITY; STANDARD; THREE DIMENSIONAL IMAGING; X RAY ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CORONARY ANGIOGRAPHY; HUMANS; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 42449085449     PISSN: 03091902     EISSN: 1464522X     Source Type: Journal    
DOI: 10.1080/03091900701775723     Document Type: Article

References (9)

1. Sundar, N., Nirmala Devi, S. and Kumaravel, N., 2006, Matched filter approach for quantification of narrowing coronary blood vessels. Proceedings of International Conference on Computer Science and its Applications, San Diego, CA, 27-29 June 2006.
2. Sangeetha, M., Nirmala Devi, S. and Kumaravel, N., 2006, Wavelet based coronary blood vessel segmentation using entrophy thresholding. The 3rd International conference on Advances in Medical Signal and Information Processing (MEDSIP 2006), Glasgow, UK, 17-19 July 2006.
3. Chow, C.K. and Kaneko, T., 1972, Automatic boundary detection of the left ventricle from cineangiograms. Computers and Biomedical Research, 5, 388-410.
4. Jiang, X. and Mojon, D., 2003, Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, 131-137.
5. Lin, C.-Y. and Ching, Y., 2005, Extraction of coronary arterial tree using cine X-ray angiograms. BioMedical Engineering, Applications, Basis and Communications, 17, 111-120.
6. Merle, A.B. Finet, G., Lienard, J. and Magnin, I.E., 1998, 3D reconstruction of the deformable coronary tree skeleton from two X-ray angiographic views. IEEE Transactions on Computers in Cardiology, 25, 757-760.
7. Serruys, W., de Feyter Jeroen Kloet, P.J., Krams, R., von Birgelen, C., van der Giessen, W.J., Cornelis, P., Slager, J., Wentzel, J.J., Schuurbiers, J.C.H. and Oomen, J.A.F., 2000, True 3-dimensional reconstruction of coronary arteries in patients by fusion of angiography and IVUS (ANGUS) and its quantitative validation. Circulation, 102, 511-516.
8. Shechter, G., Devernay, F., Coste-Manimere, E. and McVeigh, E.R., 2002, Temporal tracking of 3D coronary arteries in projection angiograms. Image Processing: Society of Photo-Optical Instrumentation Engineers Proceedings, 4684, 1-12.
9. Niessen, W., Bouma, C., Vincken, K. and Viergever, M., 2000, Error metrics for quantitative evaluation of medical image segmentation. Performance Characterization in Computer Vision (Dordrecht, The Netherlands: Kluwer Academic), pp. 275-284.