메뉴 건너뛰기




Volumn , Issue , 2012, Pages 1727-1730

Automatic differential segmentation of the prostate in 3-D MRI using Random Forest classification and graph-cuts optimization

Author keywords

Automatic Segmentation; Graph Cuts; MRI; Prostate Zones; Random Forests

Indexed keywords

AUTOMATED APPROACH; AUTOMATIC SEGMENTATIONS; BENIGN PROSTATIC HYPERPLASIA; CLASSIFICATION SCHEME; CONTEXTUAL CONSTRAINTS; GRAPH-CUTS; GROUND TRUTH; INTERACTIVE SEGMENTATION; MAGNETIC RESONANCE IMAGES; MARKOV RANDOM FIELD MODEL; PRIOR KNOWLEDGE; PROSTATE ZONES; RANDOM FOREST CLASSIFICATION; RANDOM FOREST CLASSIFIER; RANDOM FORESTS; SEMI-AUTOMATICS; SMALL TRAINING;

EID: 84864858854     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2012.6235913     Document Type: Conference Paper
Times cited : (12)

References (15)
  • 1
    • 0037454386 scopus 로고    scopus 로고
    • Benign prostatic hyperplasia
    • A. Thorpe and D. Neal, "Benign prostatic hyperplasia,"Lancet, vol. 361, no. 9366, pp. 1359-67,2003.
    • (2003) Lancet , vol.361 , Issue.9366 , pp. 1359-1367
    • Thorpe, A.1    Neal, D.2
  • 2
    • 0029242939 scopus 로고
    • Transitional zone volume and transitional zone ratio: Predictor of uroflow response to finasteride therapy in benign prostatic hyperplasia patients
    • A. Tewari, K. Shinohara and P. Narayan, "Transitional Zone Volume and Transitional Zone Ratio: Predictor of Uroflow Response to Finasteride Therapy in Benign Prostatic Hyperplasia Patients," Urology, vol. 45, no. 2, pp. 258-265, 1995.
    • (1995) Urology , vol.45 , Issue.2 , pp. 258-265
    • Tewari, A.1    Shinohara, K.2    Narayan, P.3
  • 3
    • 61849101949 scopus 로고    scopus 로고
    • Automatic 3D segmentation of prostate in MRI combining a priori knowledge, Markov fields and Bayesian framework
    • N. Makni et al, "Automatic 3D segmentation of prostate in MRI combining a priori knowledge, Markov fields and Bayesian framework," inProc. EMBS, 2008, pp. 2992-2995.
    • (2008) Proc. EMBS , pp. 2992-2995
    • Makni, N.1
  • 4
    • 41449115925 scopus 로고    scopus 로고
    • Automatic segmentation of the prostate in 3-D MR images by atlas matching using localized mutual information
    • S. Klein et al, "Automatic segmentation of the prostate in 3-D MR images by atlas matching using localized mutual information," Medical Physics, vol. 35, no. 4, pp. 1407-1417,2008.
    • (2008) Medical Physics , vol.35 , Issue.4 , pp. 1407-1417
    • Klein, S.1
  • 5
    • 80055048498 scopus 로고    scopus 로고
    • Propagating interactive segmentation of a single 3D example on similar images: An evaluation study using MR images of the prostate
    • E. Moschidis and J. Graham, "Propagating interactive segmentation of a single 3D example on similar images: an evaluation study using MR images of the prostate," in Proc. ISBI, 2011, pp. 1472-1475.
    • (2011) Proc. ISBI , pp. 1472-1475
    • Moschidis, E.1    Graham, J.2
  • 6
    • 33750955662 scopus 로고    scopus 로고
    • Differential segmentation of the prostate in MR images using combined 3D shape modelling and voxel classification
    • P. D. Allen et al, "Differential segmentation of the prostate in MR images using combined 3D shape modelling and voxel classification," in Proc. ISBI, 2006, pp. 410-13.
    • (2006) Proc. ISBI , pp. 410-413
    • Allen, P.D.1
  • 7
    • 77955214725 scopus 로고    scopus 로고
    • A systematic performance evaluation of interactive image segmentation methods based on Simulated User Interaction
    • E. Moschidis and J. Graham, "A systematic performance evaluation of interactive image segmentation methods based on Simulated User Interaction," in Proc. ISBI, 2010, pp. 928-931.
    • (2010) Proc. ISBI , pp. 928-931
    • Moschidis, E.1    Graham, J.2
  • 8
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman, "Random forests," Machine Learning, vol. 45, no. 1,pp. 5-32,2001.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 9
    • 79952311965 scopus 로고    scopus 로고
    • November. [Online]
    • A. Jaiantilal, "randomforest-matlab," November 2011. [Online]. Available: http://code.google.eom/p/randomforest-matlab/
    • (2011) Randomforest-matlab
    • Jaiantilal, A.1
  • 10
    • 84898911563 scopus 로고    scopus 로고
    • Interactive texture segmentation using random forests and total variation
    • J. Santner et al., "Interactive Texture Segmentation using Random Forests and Total Variation," in Proc. BMVC, 2009, pp. 1-12.
    • (2009) Proc. BMVC , pp. 1-12
    • Santner, J.1
  • 11
    • 0018466704 scopus 로고
    • Statistical and structural approaches to texture
    • R. M. Haralick, "Statistical and structural approaches to texture," Proc. IEEE, vol. 67, no. 5, pp. 786-804,1979.
    • (1979) Proc. IEEE , vol.67 , Issue.5 , pp. 786-804
    • Haralick, R.M.1
  • 12
    • 74849094374 scopus 로고    scopus 로고
    • A texture energy measurement technique for 3D volumetric data
    • M. T. Suzuki, Y. Yaginuma and H. Kodama, "A texture energy measurement technique for 3D volumetric data," in Proc. SMC, 2009, pp. 3779-3785.
    • (2009) Proc. SMC , pp. 3779-3785
    • Suzuki, M.T.1    Yaginuma, Y.2    Kodama, H.3
  • 14
    • 0034844730 scopus 로고    scopus 로고
    • Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images
    • Y. Boykov and M.-P. Jolly, "Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images," in Proc. ICCV, 2001, vol. 1, pp.105-112.
    • (2001) Proc. ICCV , vol.1 , pp. 105-112
    • Boykov, Y.1    Jolly, M.-P.2
  • 15
    • 4344598245 scopus 로고    scopus 로고
    • An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision
    • Y. Boykov and V. Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision,"IEEE T-PAMI, vol. 26, no. 9, pp. 1124-1137,2004.
    • (2004) IEEE T-PAMI , vol.26 , Issue.9 , pp. 1124-1137
    • Boykov, Y.1    Kolmogorov, V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.