Semi-automatic segmentation for prostate interventions

Medical Image Analysis

Volumn 15, Issue 2, 2011, Pages 226-237

  Sara Mahdavi, S ^a   Chng, Nick ^a,b   Spadinger, Ingrid ^b   Morris, William J ^b   Salcudean, Septimiu E ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b BRITISH COLUMBIA CANCER AGENCY   (Canada)

Author keywords

Prostate brachytherapy; Prostate interventions; Segmentation; Trans rectal ultrasound imaging

Indexed keywords

3-D SHAPE; BRACHYTHERAPY; BRITISH COLUMBIA; CONVEX PROBLEMS; INTRA-OBSERVER VARIABILITY; LOW DOSE RATE; MANUAL SEGMENTATION; PROSTATE BRACHYTHERAPY; PROSTATE GLANDS; PROSTATE INTERVENTIONS; PROSTATE SEGMENTATION; PROSTATE VOLUME; RADIATION ONCOLOGISTS; SEGMENTATION; SEGMENTATION ACCURACY; SEMI-AUTOMATIC SEGMENTATION; SEMI-AUTOMATICS; SHAPE FITTING; TRANS-RECTAL ULTRASOUND IMAGING; TREATMENT PLANNING; ULTRASOUND IMAGES;

DISEASES; IMAGE SEGMENTATION; ONCOLOGY; THREE DIMENSIONAL; ULTRASONICS;

RADIOTHERAPY;

ACCURACY; ALGORITHM; ANATOMICAL VARIATION; ARTICLE; BRACHYTHERAPY; CLINICAL EVALUATION; DIAGNOSTIC ERROR; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; PHYSICIAN; PRIORITY JOURNAL; PROSTATE BRACHYTHERAPY; RADIATION DOSE DISTRIBUTION; THREE DIMENSIONAL IMAGING; TRANSRECTAL ULTRASONOGRAPHY; TREATMENT PLANNING;

ALGORITHMS; BRACHYTHERAPY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MALE; PATTERN RECOGNITION, AUTOMATED; PROSTATIC NEOPLASMS; PROSTHESIS IMPLANTATION; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SURGERY, COMPUTER-ASSISTED; ULTRASONOGRAPHY, INTERVENTIONAL;

EID: 79851515705     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2010.10.002     Document Type: Article

References (33)

1. Abolmaesumi P., Sirouspour M.R. An interacting multiple model probabilistic data association filter for cavity boundary extraction from ultrasound images. IEEE Trans. Med. Imag. 2004, 23(6):772-784.
2. Badiei, S., 2007. Prostate segmentation in ultrasound images using warping and ellipsoid fitting. Master's Thesis, University of British Columbia.
3. Badiei S., Salcudean S.E., Varah J., Morris W.J. Prostate segmentation in 2D ultrasound images using image warping and ellipse fitting. Int. Conf. Med. Image Comput. Comput. Assist. Interv. LNCS 2006, 4191:17-24.
4. Bazaraa M., Sherali H., Shetty C. Nonlinear Programming: Theory and Algorithms 2006, Wiley-Interscience.
5. Boukerroui D., Baskurt A., Noble J., Basset O. Segmentation of ultrasound images - multiresolution 2D and 3D algorithm based on global and local statistics. Pattern Recogn. Lett. 2003, 24(4-5):779-790.
6. Cootes T., Taylor C., Cooper D., Graham J. Active shape models-their training and application. Comput. Vis. Image Underst. 1995, 61:38-59.
7. Ecabert O., Peters J., Schramm H., Lorenz C., von Berg J., Walker M.J., Vembar M., Olszewski M.E., Subramanyan K., Lavi G., Weese J. Automatic model-based segmentation of the heart in CT images. IEEE Trans. Med. Imag. 2008, 27(9):1189-1201.
8. Gong L., Pathak S.D., Haynor D.R., Cho P.S., Kim Y. Parametric shape modeling using deformable superellipses for prostate segmentation. IEEE Trans. Med. Imag. 2004, 23(3):340-349.
9. Halpern E.J., Cochlin D.L., Goldberg B.B. Imaging of the Prostate 2002, Martin Dunitz.
10. Hodge A.C., Fenster A., Downey D.B., Ladak H.M. Prostate boundary segmentation from ultrasound images using 2D active shape models: optimisation and extension to 3D. Comput. Methods Prog. Biomed. 2006, 84(2-3):99-113.
11. Hu N., Downey D.B., Fenster A., Ladak H.M. Prostate boundary segmentation from 3D ultrasound images. Med. Phys. 2003, 30(7):1648-1659.
12. Huang X., Metaxas D.N. Metamorphs: deformable shape and appearance models. IEEE Trans. Pattern Anal. Mach. Intell. 2008, 30(8):1444-1459.
13. Jendoubi, A., Zeng, J., Chouikha, M., 2004. Top-down approach to segmentation of prostate boundaries in ultrasound images. In: Applied Imagery Pattern Recognition Workshop, 2004. Proceedings of 33rd. pp. 145-149.
14. Kachouie, N.N., Fieguth, P., Rahnamayan, S., August 2006. An elliptical level set method for automatic TRUS prostate image segmentation. In: Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, pp. 191-196.
15. Ladak H.M., Mao F., Wang Y., Downey D.B., Steinman D.A., Fenster A. Prostate boundary segmentation from 2D ultrasound images. Med. Phys. 2000, 27(8):1777-1788.
16. Mahdavi S., Salcudean S.E. 3D prostate segmentation based on ellipsoid fitting, image tapering and warping. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2008, 1:2988-2991.
17. Mahdavi S.S., Morris W.J., Spadinger I., Chng N., Goksel O., Salcudean S.E. 3D prostate segmentation in ultrasound images based on tapered and deformed ellipsoids. Med. Image Comput. Comput. Assist. Interv. LNCS 2009, 5762(Pt 2):960-967.
18. Morris W.J., Keyes M., Palma D., Spadinger I., McKenzie M.R., Agranovich A., Pickles T., Liu M., Kwan W., Wu J., Berthelet E., Pai H. Population-based study of biochemical and survival outcomes after permanent 125 I brachytherapy for low- and intermediate-risk prostate cancer. Urology 2009, 73(4):860-865. (discussion 865-7).
19. Nag S., Ciezki J.P., Cormack R., Doggett S., DeWyngaert K., Edmundson G.K., Stock R.G., Stone N.N., Yu Y., Zelefsky M.J. Intraoperative planning and evaluation of permanent prostate brachytherapy: report of the american brachytherapy society. Int. J. Radiat. Oncol. Biol. Phys. 2001, 51(5):1422-1430. Clinical Research Committe, A.B.S.
20. Nanayakkara N.D., Samarabandu J., Fenster A. Prostate segmentation by feature enhancement using domain knowledge and adaptive region-based operations. Phys. Med. Biol. 2006, 51(7):1831-1848.
21. Nascimento J.C., Marques J.S. Robust shape tracking with multiple models in ultrasound images. IEEE Trans. Image Process. 2008, 17(3):392-406.
22. Noble J.A., Boukerroui D. Ultrasound image segmentation: a survey. IEEE Trans. Med. Imag. 2006, 25(8):987-1010.
23. Pathak S.D., Haynor D.R., Kim Y. Edge-guided boundary delineation in prostate ultrasound images. IEEE Trans. Med. Imag. 2000, 19(12):1211-1219.
24. Penna M.A., Dines K.A., Seip R., Carlson R.F., Sanghvi N.T. Modeling prostate anatomy from multiple view TRUS images for image-guided HIFU therapy. IEEE Trans. Ultrason Ferr. Freq. Control 2007, 54(1):52-69.
25. Pluempitiwiriyawej C., Moura J.M.F., Fellow, Wu Y.-J.L., Ho C. STACS: new active contour scheme for cardiac MR image segmentation. IEEE Trans. Med. Imag. 2005, 24(5):593-603.
26. Shen D., Zhan Y., Davatzikos C. Segmentation of prostate boundaries from ultrasound images using statistical shape model. IEEE Trans. Med. Imag. 2003, 22(4):539-551.
27. Thevenaz P., Unser M. Snakuscules. IEEE Trans. Image Process. 2008, 17(4):585-593.
28. Tutar I.B., Pathak S.D., Gong L., Cho P.S., Wallner K., Kim Y. Semiautomatic 3-D prostate segmentation from TRUS images using spherical harmonics. IEEE Trans. Med. Imag. 2006, 25(12):1645-1654.
29. Varah J.M. Least squares data fitting with implicit functions. BIT 1996, 36(4):842-854.
30. Yezzi A., Kichenassamy S., Kumar A., Olver P., Tannenbaum A. A geometric snake model for segmentation of medical imagery. IEEE Trans. Med. Imag. 1997, 16(2):199-209.
31. Zaim, A., 2008. An edge-based approach for segmentation of prostate ultrasound images using phase symmetry. In: ISCCSP 2008. pp. 10-13.
32. Zhan Y., Shen D. Deformable segmentation of 3-D ultrasound prostate images using statistical texture matching method. IEEE Trans. Med. Imag. 2006, 25(3):256-272.
33. Zhan Y., Shen D., Zeng J., Sun L., Fichtinger G., Moul J., Davatzikos C. Targeted prostate biopsy using statistical image analysis. IEEE Trans. Med. Imag. 2007, 26(6):779-788.