Prostate cancer characterization on MR images using fractal features

Medical Physics

Volumn 38, Issue 1, 2011, Pages 83-95

  Lopes, R ^a   Ayache, A ^b   Makni, N ^a   Puech, P ^a,c   Villers, A ^a,c   Mordon, S ^a   Betrouni, N ^a  

^a UNIV LILLE   (France)

^b UNIVERSITÉ LILLE 1   (France)

^c LILLE UNIVERSITY HOSPITAL   (France)

Author keywords

classification; fractal and multifractal; peripheral zone; prostate cancer; T2 weighted MR

Indexed keywords

ADAPTIVE BOOSTING; DISEASES; FRACTAL DIMENSION; GABOR FILTERS; MAGNETIC RESONANCE IMAGING; SUPPORT VECTOR MACHINES; TEXTURES; UROLOGY;

CLASSIFICATION ALGORITHM; CLASSIFICATION RESULTS; MULTI FRACTALS; MULTIFRACTIONAL BROWNIAN MOTION; PROSTATE CANCERS; SIGNAL INTENSITY VARIATIONS; SUPERVISED CLASSIFICATION; T2 WEIGHTED;

CLASSIFICATION (OF INFORMATION);

EID: 78650889076     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3521470     Document Type: Article

References (61)

1. P. Kozlowski, S. D. Chang, E. C. Jones, K. W. Berean, H. Chen, and S. L. Goldenberg, " Combined diffusion-weighted and dynamic contrast-enhanced MRI for prostate cancer diagnosis correlation with biopsy and histopathology., " J. Magn. Reson Imaging 1053-1807 24, 108-113 (2006). 10.1002/jmri.20626
2. A. Villers, L. Lemaitre, J. Haffner, and P. Puech, " Current status of MRI for the diagnosis, staging and prognosis of prostate cancer: Implications for focal therapy and active surveillance.," Curr. Opin. Urol. 19 (3), 274-282 (2009). 10.1097/MOU.0b013e328329a2ed 0963-0643
3. I. Chan, W. Wells, R. V. Mulkern, S. Haker, J. Zhang, K. H. Zou, S. E. Maier, and C. Tempany, " Detection of prostate cancer by integration of line-scan diffusion, T2-mapping and T2-weighted magnetic resonance imaging: A multichannel statistical classifier.," Med. Phys. 0094-2405 30 (9), 2390-2398 (2003). 10.1118/1.1593633 (Pubitemid 37129745)
4. A. Madabhushi, M. D. Feldman, M. D. Metaxas, J. Tomaszeweski, and D. Chute, " Automated detection of prostatic adenocarcinoma from high resolution ex vivo MRI.," IEEE Trans. Med. Imaging 0278-0062 24 (12), 1611-1625 (2005). 10.1109/TMI.2005.859208 (Pubitemid 41812028)
5. T. R. Reed and J. M. Hans Du Buf, " A review of recent texture segmentation and feature extraction techniques.," CVGIP: Image Understand. 1049-9660 57 (3), 359-372 (1993). 10.1006/ciun.1993.1024
6. X. Liu, D. L. Langer, M. A. Haider, Y. Yang, M. N. Wermick, and I. S. Yetik, " Prostate cancer segmentation with simultaneous estimation of Markov random field parameters and class.," IEEE Trans. Med. Imaging 0278-0062 28 (6), 906-915 (2009). 10.1109/TMI.2009.2012888
7. D. Lv, X. Guo, X. Wang, J. Zhang, and J. Fang, " Computerized characterization of prostate cancer by fractal analysis in MR images.," J. Magn. Reson Imaging 1053-1807 30, 161-168 (2009). 10.1002/jmri.21819
8. P. Puech, N. Betrouni, N. Makni, A. S. Dewalle, A. Villers, and L. Lemaitre, " Computer assisted diagnosis of prostate cancer using DCE-MRI data: Design, implementation and preliminary results.," Int. J. CARS 4 (1), 1-10 (2009). 10.1007/s11548-008-0261-2 1861-6429
9. C. G. Berman and N. J. Brodsky, " Prostate cancer imaging.," Cancer Control 1073-2748 5, 541-554 (1998).
10. M. L. Schiebler, J. E. Tomaszewski, M. Bezzi, H. M. Pollack, H. Y. Kressel, and E. K. Cohen, " Prostatic carcinoma and benign prostatic hyperplasia: Correlation of high-resolution MR and histopathologic findings.," Radiology 0033-8419 172, 131-137 (1989).
11. A. Br, D. Casero, S. Franciscis, and M. A. Herrero, " Fractal analysis and tumour growth.," Math. Comput. Modell. 0895-7177 47 (5-6), 546-559 (2008). 10.1016/j.mcm.2007.02.033 (Pubitemid 351199979)
12. J. M. Zook and K. M. Iftekharuddin, " Statistical analysis of fractal-based brain tumor detection algorithms.," Magn. Reson. Imaging 0730-725X 23, 671-678 (2005). 10.1016/j.mri.2005.04.002 (Pubitemid 41033045)
13. B. Mandelbrot and J. W. Van Ness, " Fractional Brownian motion, fractional noises and applications., SIAM Rev. 0036-1445 10 (4), 422-438 (1968). 10.1137/1010093
14. A. P. Pentland, " Fractal-based description of natural scenes.," IEEE Trans. Pattern Anal. Mach. Intell. 0162-8828 PAMI-6, 661-674 (1984). 10.1109/TPAMI.1984.4767591
15. R. Jennane, R. Harba, G. Lemineur, S. Bretteil, A. Estrade, and C. L. Benhamou, " Estimation of the 3D self-similarity parameter of trabecular bone from its 2D projection.," Med. Image Anal. 1361-8415 11, 91-98 (2007). 10.1016/j.media.2006.11.001 (Pubitemid 46202205)
16. M. E. Mavroforakis, H. V. Georgiou, N. Dimitropoulos, D. Cavouras, and S. Theodoridis, " Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiers.," Artif. Intell. Med. 0933-3657 37, 145-162 (2006). 10.1016/j.artmed.2006.03.002 (Pubitemid 43816282)
17. K. M. Iftekharuddin, J. Zheng, M. A. Islam, and R. J. Ogg, " Fractal-based brain tumor detection in multimodal MRI.," Appl. Math. Comput. 0096-3003 207 (1), 23-41 (2009). 10.1016/j.amc.2007.10.063
18. A. Benassi, S. Jaffard, and D. Roux, " Gaussian processes and pseudodifferential elliptic operators.," Revista Mathematica Iberoamericana 13 (1), 19-81 (1997).
19. R. F. Peltier and J. Ĺvy V́hel, " Multifractional Brownian motion: Definition and preliminary results.," Technical Report of INRIA No. 2645, 1995.
20. A. Islam, K. M. Iftekharuddin, R. J. Ogg, F. Laningham, and B. Sivakumar, " Multifractal modeling, segmentation, prediction and statistical validation of posterior fossa tumors.," in Proceedings of SPIE Medical Imaging: Computer-Aided Diagnosis Vol. 6915, pp. 1-11, 2008 (unpublished).
21. J. -M. Bardet, G. Lang, G. Oppenheim, A. Philippe, and M. S. Taqqu, Long-Range Dependence, theory and applications (Birkhäuser, Basel, Switzerland, 2003).
22. P. Embrechts and M. Maejima, Self-Similar Processes (Princeton University Press, New Jersey, 2002).
23. B. B. Mandebrot, Fractals and Scaling in Finance: Discontinuity, Concentration, Risk (Springer-Verlag, New York, 1997).
24. B. B. Mandebrot, Fractales, Hasard et Finance (Flammarion, Paris, 1997).
25. S. Jaffard, Y. Meyer, and R. Ryan, Wavelets Tools for Science & Technology (SIAM Society for Industrial and Applied Mathematics, Philadelphia, PA, 2001).
26. A. Ayache, " Du mouvement Brownien fractionnaire au mouvement Brownien multifractionnaire (article de synth̀se).," Techniques et Sciences Informatiques 20 (9), 1132-1152 (2001).
27. P. Goņalv̀s and P. Abry, " Multiple-window wavelet transform and local scaling exponent estimation.," in Proceedings of the Conference ICASSP, pp. 3433-3436, 1997 (unpublished).
28. A. Ayache, C. Cohen, and J. Ĺvy V́hel, " The covariance structure of multifractional Brownian motion.," in Proceedings of the Conference ICASSP, 2000 (unpublished).
29. R. Lopes and N. Betrouni, " Fractal and multifractal analysis: A review.," Med. Image Anal. 1361-8415 13 (4), 634-649 (2009). 10.1016/j.media.2009.05.003
30. K. M. Iftekharuddin and C. Parra, " Multiresolution fractal feature extraction and tumor detection: Analytical model and implementation.," in Proceedings of SPIE Wavelets: Applications in Signal and Image Processing, Vol. 5207, 2003 (unpublished).
31. R. J. Adler, The Geometry of Random Fields (Wiley, London, 1981).
32. S. Mallat, A Wavelet Tour of Image Processing (Academic, New York, 1998).
33. P. Abry, P. Flandrin, M. Taqqu, and D. Veitch, " Self-similarity and long-range dependence through the wavelet lens.," Long-Range Dependence: Theory and Applications (Birkhäuser, Boston, 2003), pp. 527-556.
34. A. Benassi, C. Cohen, and J. Istas, " Identifying the multifractional function of a Gaussian process.," Stat. Probab. Lett. 0167-7152 39, 337-345 (1998). 10.1016/S0167-7152(98)00078-9
35. A. Gloter and M. Hoffman, " Estimation of the Hurst parameters from discrete noisy data.," Ann. Stat. 0090-5364 35, 1947-1974 (2007). 10.1214/009053607000000316
36. V. Vapnik, The Nature of Statistical Learning Theory (Springer-Verlag, New York, 1995).
37. M. Pontil and A. Verri, " A support vector machines for 3D object recognition.," IEEE Trans. Pattern Anal. Mach. Intell. 0162-8828 20 (6), 637-646 (1998). 10.1109/34.683777 (Pubitemid 128744848)
38. G. Yu, G. Ostrouchov, A. Geist, and N. Samatova, " A SVM-based algorithm for identification of photosynthesis-specific genome features.," in Proceedings of IEEE Computer Society Bioinformatics Conference, pp. 235-243, 2003 (unpublished).
39. H. Liu, R. Zhang, F. Luan, X. Yao, M. Liu, and Z. Hu, " Diagnosing breast cancer based on support vector machines.," J. Chem. Inf. Comput. Sci. 0095-2338 43 (3), 900-907 (2003). 10.1021/ci0256438
40. R. Duda, P. Hart, and D. Stork, Pattern Classification (Wiley, New York, 2001).
41. Y. Freund and R. Schapire, " Experiments with a new boosting algorithm.," in Proceedings of 13th International Conference on Machine Learning, pp. 148-156, 1999 (unpublished).
42. A. Vezhnevets and V. Vezhnevets, " Modest AdaBoost-Teaching AdaBoost to generalize better.," in Proceedings of GraphiCon, Vol. 12, pp. 987-997, 2005 (unpublished).
43. R. Schapire and Y. Singer, " Improved boosting algorithms using confidence-rated predictions.," Mach. Learn. 0885-6125 37, 297-336 (1999). 10.1023/A:1007614523901 (Pubitemid 32210620)
44. J. Friedman, T. Hastie, and R. Tibshirani, " Additive logistic regression: A statistical view of boosting.," Ann. Stat. 0090-5364 28 (2), 337-407 (2000). 10.1214/aos/1016218223
45. J. E. McNeal and O. Haillot, " Patterns of spread of adenocarcinoma in the prostate as related to cancer volume.," Prostate 0270-4137 49, 48-57 (2001). 10.1002/pros.1117 (Pubitemid 32807947)
46. J. McNeal, A. Villers, E. A. Redwine, F. Freiha, and T. Stamey, " Histologic differentiation, cancer volume and pelvic lymph node metastasis in adenocarcinoma of prostate.," Cancer 0008-543X 66, 1225-1233 (1990). 10.1002/1097-0142(19900915)66:6<1225::AID-CNCR2820660624>3.0.CO;2-X
47. J. Haffner, E. Potiron, S. Bouý, P. Puech, X. Leroy, L. Lemaitre, and A. Villers, " Peripheral zone prostate cancers: Location and intraprostatic patterns of sprea at histology.," Eur. Urol. 0302-2838 69, 276-282 (2009).
48. A. Villers, P. Puech, D. Mouton, X. Leroy, C. Ballereau, and L. Lemaitre, " Dynamic contrast enhanced, pelvic phased array magnetic resonance imaging of localized cancer for predicting tumor volume: Correlation with radical prostatectomy findings.," J. Urol. (Paris) 0248-0018 176, 2432-2437 (2006). 10.1016/j.juro.2006.08.007 (Pubitemid 44665992)
49. A. Alvarenga, W. Pereira, A. Infantosi, and C. Azevedo, " Complexity curve and grey level cooccurrence matrix in the texture evaluation of breast tumor on ultrasound images.," Med. Phys. 0094-2405 34 (2), 379-387 (2007). 10.1118/1.2401039 (Pubitemid 46185116)
50. H. Chan, D. Wei, M. Lelvie, B. Sahiner, D. Adler, M. Goodsitt, and N. Petrick, " Computer aided classification of mammographic masses and normal tissue: Linear discriminant analysis in texture feature space.," Phys. Med. Biol. 0031-9155 40, 857-876 (1995). 10.1088/0031-9155/40/5/010
51. D. Mahmoud-Ghoneim, G. Toussaint, J. M. Constans, and J. De Certaines, " Three dimensional texture analysis in MRI: A preliminary evaluation in gliomas.," Magn. Reson. Imaging 0730-725X 21 (9), 983-987 (2003). 10.1016/S0730-725X(03)00201-7 (Pubitemid 37549858)
52. R. Haralick, K. Shanmugan, and I. Dinstein, " Textural features for image classification.," IEEE Trans. Syst. Man Cybern. 0018-9472 3, 610-621 (1973). 10.1109/TSMC.1973.4309314
53. A. K. Jain and F. Farrokhnia, " Unsupervised texture segmentation using Gabor filters.," Pattern Recogn. 0031-3203 24 (12), 1167-1186 (1991). 10.1016/0031-3203(91)90143-S
54. Z. Qian, D. Metaxas, and L. Axel, " Extraction and tracking of MRI tagging sheets using a 3D Gabor filter bank.," in Proceedings of the IEEE Engineering in Medicine and Biology Society, pp. 711-714, 2006 (unpublished).
55. M. Unser, " Texture classification and segmentation using wavelet frames.," IEEE Trans. Image Process. 1057-7149 4 (11), 1549-1560 (1995). 10.1109/83.469936
56. A. Madabhushi and J. K. Udupa, " Interplay between intensity standardization and inhomogeneity correction in MR image processing.," IEEE Trans. Med. Imaging 0278-0062 24 (5), 561-576 (2005). 10.1109/TMI.2004.843256 (Pubitemid 40680118)
57. A. Pizurica, W. Philips, I. Lemahieu, and M. Acheroy, " A versatile wavelet domain noise filtration technique for medical imaging.," IEEE Trans. Med. Imaging 0278-0062 22 (3), 323-331 (2003). 10.1109/TMI.2003.809588
58. T. Pavlidis, " A review of algorithms for shape analysis.," Comput. Graph. Image Process. 0146-664X 7, 243-258 (1978). 10.1016/0146-664X(78) 90115-6
59. P. Kestener, J. Lina, P. Saint-Jean, and A. Arneodo, " Wavelet-based multifractal formalism to assist in diagnosis in digitized mammograms.," Image Anal. Stereol. 20 (3), 169-175 (2004). 1580-3139
60. M. I. Khalil and M. M. Bayoumi, " Invariant 2D object recognition using the wavelet modulus maxima.," Pattern Recogn. Lett. 0167-8655 21 (9), 863-872 (2000). 10.1016/S0167-8655(00)00046-5
61. J. Ĺvy V́hel, " Traitement fractal et multifractal des images.," Trait. Signal 0765-0019 20 (3), 303-311 (2003).