Texture-based tissue characterization for high-resolution CT scans of coronary arteries

Communications in Numerical Methods in Engineering

Volumn 25, Issue 6, 2009, Pages 597-613

  Papadakis, Manos ^a   Bodmann, Bernhard G ^a   Alexander, Simon K ^a   Vela, Deborah ^b,c   Baid, Shikha ^a   Gittens, Alex A ^d   Kouri, Donald J ^a   Gertz, S David ^e   Jain, Saurabh ^a   Romero, Juan R ^f   Li, Xiao ^a   Cherukuri, Paul ^g   Cody, Dianna D ^h   Gladish, Gregory W ^h   Aboshady, Ibrahim ^b,c   Conyers, Jodie L ^b,c   Casscells, S Ward ^b,c  

^a UNIVERSITY OF HOUSTON   (United States)

^b UNIVERSITY OF TEXAS   (United States)

^c TEXAS HEART INSTITUTE   (United States)

^d CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^e HEBREW UNIVERSITY   (Israel)

^f UNIVERSITY OF PUERTO RICO   (Puerto Rico)

^g RICE UNIVERSITY   (United States)

^h UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

Author keywords

Biomedical imaging; Isotropic multiresolution; Statistical discrimination; Textures; Wavelets

Indexed keywords

BIOMEDICAL IMAGING; COMPUTED TOMOGRAPHY; CORONARY ARTERIES; CT SCAN; CT VOLUME; HIGH RESOLUTION; HIGH RESOLUTION CT; IMAGE ENCODING; ISOTROPIC MULTIRESOLUTION; MULTIRESOLUTION WAVELETS; STATISTICAL DISCRIMINATION; TISSUE CHARACTERIZATION; WAVELET ALGORITHMS; WAVELET REPRESENTATION; WAVELETS;

COMPUTERIZED TOMOGRAPHY; MULTIRESOLUTION ANALYSIS;

TEXTURES;

EID: 67349092655     PISSN: 10698299     EISSN: 10990887     Source Type: Journal    
DOI: 10.1002/cnm.1189     Document Type: Article

References (30)

1. Bamberg F, Dannemann N, Shapiro M, Seneviratne S, Ferencik M, Butler J, Koenig W, Nasir K, Cury R, Tawakol A et al. Association between cardiovascular risk profiles and the presence and extent of different types of coronary atherosclerotic plaque as detected by multidetector computed tomography. Arteriosclerosis, Thrombosis, and Vascular Biology 2008; 28(3):568-574.
2. Schroeder S, Kuettner A, Wojak T, Janzen J, Heuschmid M, Athanasiou T, Beck T, Burgstahler C, Herdeg C, Claussen C et al. Non-invasive evaluation of atherosclerosis with contrast enhanced 16 slice spiral computed tomography: results of ex vivo investigations. Heart 2004; 90(12):1471-1475.
3. Schoenhagen P, Halliburton S, Stillman A, Kuzmiak S, Nissen S, Tuzcu E, White R. Noninvasive imaging of coronary arteries: current and future role of multi-detector row CT. Radiology 2004; 232(1):7-17.
4. Gertz SD, Bodmann BG, Vela D, Papadakis M, Aboshady I, Cherukuri P, Alexander S, Kouri DJ, Baid S, Gittens AA et al. Three-dimensional isotropic wavelets for post-acquisitional extraction of latent images of atherosclerotic plaque components from micro-computed tomography of human coronary arteries. Academic Radiology 2007; 14:1509-1519.
5. Ross W, Cody D, Hazle J. Design and performance characteristics of a digital flat-panel computed tomography system. Medical Physics 2006; 33(6):1888-1901.
6. Naghavi M, Libby P, Falk E, Casscells S, Litovsky S, Rumberger J, Badimon J, Stefanadis C et al. From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: Part I. Circulation 2003; 108(14):1664-1672.
7. Naghavi M, Libby P, Falk E, Casscells S, Litovsky S, Rumberger J, Badimon J, Stefanadis C et al. From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: Part II. Circulation 2003; 18(15):1772-1778.
8. Cuadra M, Cammoun L, Butz T, Cuisenare O, Thiran JP. Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images. IEEE Transactions on Medical Imaging 2005; 24(12):1548-1565.
9. Greenspan H, Ruf A, Goldberger J. Constrained Gaussian mixture model framework for automatic segmentation of MR-brain images. IEEE Transactions on Medical Imaging 2006; 24(12):1233-1245.
10. Jeong J, Shin D, Do S, Marmarelis V. Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomography. IEEE Transactions on Medical Imaging 2006; 25(8):1068-1078.
11. Do M, Vetterli M. Rotation invariant texture characterization and retrieval using steerable wavelet domain hidden Markov models. IEEE Transactions on Multimedia 2002; 4(4):517-527.
12. Cardinal MH, Meunier J, Soulez G, Maurice R, Therasse E, Cloutier G. Intravascular ultrasound image segmentation: a three-dimensional fast-marching method based on gray level distributions. IEEE Transactions on Medical Imaging 2006; 25(5):590-601.
13. Salem MAM, Tolba MF, Mostafa MG, Gharib TF. Mr-brain image segmentation using gaussian multiresolution analysis and the EM algorithm. ACM-IEEE 8th International Conference of Enterprise Intelligent Computing, vol. 2, Angers, France, 2003; 165-170.
14. Arivazhagan S, Ganesan L, Kumar TGS. Texture classification using curvelet statistical and co-occurrence features. ICPR 06: Proceedings of the 18th International Conference on Pattern Recognition. IEEE Computer Society: Washington, DC, U.S.A., 2006; 938-941.
15. Sagiv C, Sochen N, Zeevi Y. Integrated active contours for texture segmentation. IEEE Transactions on Image Processing 2006; 15(6):1633-1646.
16. Zhu SC, Wu Y, Mumford D. Filters, random fields and maximum entropy (frame): towards a unified theory for texture modeling. International Journal of Computer Vision 1998; 27(2):107-126.
17. Mumford D, Gidas B. Stochastic models for generic images. Technical Report, Brown University, 1998.
18. Azencott R, Graffigne C, Labourdette C. Edge Detection and Segmentation of Textured Images using Markov Fields. Lecture Notes in Statistics, vol. 74. Springer: Berlin, 1992; 75-88.
19. Azencott R, Graffigne C. Non supervised image segmentation and multi-scale Markov random fields. 11th IAPR Congress on Image Speech and Signal analysis, La Haye, 1992; 201-204.
20. Azencott R (ed.). Simulated Annealing: Parallelization Techniques. Wiley Interscience: New York, 1992.
21. Paget R, Longstaff I. Texture synthesis via nonparametric multiscale Markov random field. IEEE Transactions on Image Processing 1998; 7(6):925-931.
22. Portilla J, Strela V, Wainwright M, Simoncelli E. Image denoising using Gaussian scale mixtures in the wavelet domain. IEEE Transactions on Image Processing 2003; 12(11):1338-1351. Computer Science Technical Report Number TR2002-831, Courant Institute of Mathematical Sciences.
23. Srivastava A, Lee AB, Simoncelli EP, Zhu SC. On advances in statistical modeling of natural images. Journal of Mathematical Imaging and Vision 2003; 18(1):17-33.
24. Papadakis M, Gogoshin G, Kakadiaris I, Kouri D, Hoffman D. Non-separable radial frame multiresolution analysis in multidimensions. Numerical Functional Analysis and Optimization 2003; 24:907-928.
25. Romero JR, Alexander SK, Baid S, Jain S, Papadakis M. The geometry and the analytic properties of Isotropic Multiresolution Analysis. Advances in Computational Mathematics 2009; in press.
26. Casazza P. The art of frame theory. Taiwanese Journal of Mathematics 2000; 4:129-201.
27. Bodmann B, Papadakis M, Kouri D, Gertz S, Cherukuri P, Vela D, Gladish G, Cody D, Aboshady I, Conyers J et al. Frame isotropic multiresolution analysis for micro CT scans of coronary arteries. In Wavelets XI, Papadakis M, Laine A, Unser M (eds), vol. 5914. SPIE: 2005; 59 141O/1-12.
28. Murashige A, Hiro T, Fujii T, Imoto K, Murata T, Fukumoto Y, Matsuzaki M. Detection of lipid-laden atherosclerotic plaque by wavelet analysis of radiofrequency intravascular ultrasound signals in vitro validation and preliminary in vivo application. Journal of the American College of Cardiology 2005; 45:1954-1960.
29. Breiman L. Probability. Classics in Applied Mathematics. SIAM: Philadelphia, PA, 1992.
30. Conway J. A Course in Operator Theory. Graduate Studies in Mathematics, vol. 21. American Mathematical Society: Providence, RI, 2000.