Improved technique to detect the infarction in delayed enhancement image using k-mean method

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

Volumn 6112 LNCS, Issue PART 2, 2010, Pages 108-119

  Metwally, Mohamed K ^a   El Gayar, Neamat ^a   Osman, Nael F ^a,b  

^a NILE UNIVERSITY   (Egypt)

^b JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Cardiac Magnetic resonance; Delayed Enhancement; k means clustering technique

Indexed keywords

CARDIAC MAGNETIC RESONANCE; COMBINED MEASURE; CONTRAST AGENT; CONTRAST TO NOISE RATIO; EXISTING METHOD; F-SCORE; K-MEANS CLUSTERING; K-MEANS CLUSTERING TECHNIQUES; NOISY IMAGE; REAL IMAGES; THRESHOLDING;

COMPUTER SIMULATION; HEART; IMAGE ANALYSIS; MAGNETIC MATERIALS; MAGNETIC RESONANCE; WATER SUPPLY SYSTEMS;

IMAGE SEGMENTATION;

EID: 77955402116     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-13775-4_12     Document Type: Conference Paper

References (14)

1. Pham, D.L., Xu, C., Prince, J.L.: Current Methods in Medical Image Segmentation. Annual Reviews 2, 315-338 (2000)
2. Hsu, L.-Y., Natanzon, A., Kellman, P., Hirsch, G.A., Aletras, A.H., Arai, A.E.: Quantitative Myocardial Infarction on Delayed Enhancement MRI. Part I: Animal Validation of an Automated Feature Analysis and Combined Thresholding Infarct Sizing Algorithm. J. Magn. Reson. Imaging 23(3), 298-308 (2006)
3. Kolipaka, A., Chatzimavroudis, G.P., White, R.D., ODonnell, T.P., Randolph, M.: Segmentation of non-viable myocardium in delayed enhancement magnetic resonance images. The International Journal of Cardiovascular Imaging (formerly Cardiac Imaging) 21, 303-311 (2005) (Pubitemid 40895339)
4. Doublier, C., Couprie, M., Garot, J., Hamam, Y.: Computer assisted segmentation, quantification and visualization of an infarcted myocardium from MRI images. Biomedsim. 3, 151-156 (2003)
5. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, pp. 526-528. Wiley, New York (1973)
6. Hood, M.: Overview of delayed myocardial enhancement in cardiac MRI (February 12, 2009), http://www.ismrm.org/smrt/09/mock-clinical-poster-Mo.pdf
7. Sijbers, J., Den, D.A.J., Van, D.D., Raman, E.: Estimation of signal and noise from Rician distributed data. In: Proc. Int. Conf. Signal Proc. and Comm., Spain, pp. 140-142 (1998)
8. Gonzalez, R.C., Wood, R.E.: Digital Image Processing, pp. 147-175. Prentice-Hall, Englewood Cliffs (2002)
9. Beitzel, S.M.: On Understanding And Classifying Web Queries, Chicago, Illinois (May 2006)
10. Zumel, N.: Statistics to English Translation, Part 1: Accuracy Measures (November 3, 2009), http://win-vector.com/dfiles/StatisticsToEnglishPart1- Accuracy.pdf
11. Marina, S., Nathalie, J., Stan, S.: Beyond Accuracy, F-score and ROC: a Family of Discriminant Measures for Performance Evaluation. In: Australian Conference on Artificial Intelligence (2006)
12. Sievers, B., Rehwald, W.G., Albert, T.S., Patel, M.R., Parker, M.A., Kim, R.J., Judd, R.M.: Respiratory Motion and Cardiac Arrhythmia Effects on Diagnostic Accuracy of Myocardial Delayed-enhanced MR Imaging in Canines. Radiology 247, 106-114 (2008)
13. Bernhard, K., Michael, F., Tobias, H., Uwe, H., Albertus, S., Claus, C., Stephan, M.: Assessment of myocardial viability using delayed enhancement magnetic resonance imaging at 3.0 tesla. Investigative Radiology 41, 661-667 (2006)
14. Thompson, M.: November 21 (2003), http://www.phys.cwru.edu/courses/p431/ notes-2003/node123.html