Global localization of 3D anatomical structures by pre-filtered Hough Forests and discrete optimization

Medical Image Analysis

Volumn 17, Issue 8, 2013, Pages 1304-1314

  Donner, René ^a,b   Menze, Bjoern H ^c,d,e   Bischof, Horst ^b   Langs, Georg ^a,c  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

^b GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^d INRIA   (France)

^e ETH ZURICH   (Switzerland)

Author keywords

Anatomical structure localization; Hough regression; Interest point detection; Random Forests

Indexed keywords

ANATOMICAL STRUCTURES; AUTOMATIC LOCALIZATION; DISCRETE OPTIMIZATION; DISCRETE OPTIMIZATION PROBLEMS; HOUGH REGRESSION; INTEREST POINT DETECTIONS; NEIGHBORHOOD INFORMATION; RANDOM FORESTS;

DECISION TREES; ENCODING (SYMBOLS); GEOMETRY; MARKOV PROCESSES; OPTIMIZATION; REGRESSION ANALYSIS;

TOPOLOGY;

ANATOMIC LANDMARK; ANATOMICAL CONCEPTS; ARTICLE; CLASSIFIER; FILTRATION; HAND; HUMAN; PRIORITY JOURNAL; PROBABILITY; RANDOM FOREST; TRAINING; WEIGHT; WHOLE BODY CT; X RAY FILM;

ANATOMICAL STRUCTURE LOCALIZATION; HOUGH REGRESSION; INTEREST POINT DETECTION; RANDOM FORESTS;

ALGORITHMS; ANATOMIC LANDMARKS; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED; WHOLE BODY IMAGING;

EID: 84884978733     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2013.02.004     Document Type: Article

References (43)

1. Andres, B., Kappes, J.H., Koethe, U., Schnörr, C., Hamprecht, F.A., 2010. An empirical comparison of inference algorithms for graphical models with higher order factors using OpenGM. In: Proc. of DAGM 2010, pp. 353-362.
2. Bergtholdt M., Kappes J., Schmidt S., Schnörr C. A study of parts-based object class detection using complete graphs. IJCV 2010, 87:93-117.
3. Breiman, L., 2001. Random forests. Machine Learning, 5-32.
4. Boykov Y., Veksler O., Zabih R. Fast approximate energy minimization via graph cuts. TPAMI 2001, 23:1222-1239.
5. Cheng Y. Mean shift, mode seeking, and clustering. TPAMI 1995, 17:790-799.
6. Cootes T.F., Taylor C.J., Cooper D.H., Graha J. Active shape models - their training and application. CVIU 1995, 61:38-59.
7. Cootes T.F., Edwards G.J., Taylor C.J. Active appearance models. TPAMI 2001, 23:681-685.
8. Cremers D., Rousson M., Deriche R. A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape. IJCV 2007, 72:195-215.
9. Criminisi, A., Shotton, J., Bucciarelli, S., 2009. Decision forests with long-range spatial context for organ localization in CT volumes. In: Proc. of MICCAI workshop on Probabilistic Models for Medical Image Analysis (MICCAI-PMMIA).
10. Criminisi, A., Shotton, J., Robertson, D., Konukoglu, E., 2010. Regression forests for efficient anatomy detection and localization in ct studies. In: Medical Computer Vision 2010: Recognition Techniques and Applications in Medical Imaging, MICCAI Workshop, pp. 106-117.
11. de Bruijne, M., Nielsen, M., 2004. Shape particle filtering for image segmentation. In: Proc. MICCAI, pp. 168-175.
12. Dittrich, E., Riklin-Raviv, T., Kasprian, G., Brugger, P., Prayer, D., Langs, G., 2011. Learning a spatio-temporal latent atlas for fetal brain segmentation. In: Proceedings of MICCAI Workshop on Image Analysis of Human Brain Development.
13. Doi K. Computer-aided diagnosis in medical imaging: historical review, current status and future potential. Computerized Medical Imaging and Graphics 2007, 31:198-211.
14. Donner, R., Mičušík, B., Langs, G., Bischof, H., 2007a. Sparse MRF appearance models for fast anatomical structure localisation. In: Proc. BMVC.
15. Donner, R., Mičušík, B., Langs, G., Szumilas, L., Peloschek, P., Friedrich, K., Bischof, H., 2007b. Object localization based on markov random fields and symmetry interest points. In: Proc. MICCAI, pp. 460-468.
16. Donner, R., Wildenauer, H., Bischof, H., Langs, G., 2009. Weakly supervised group-wise model learning based on discrete optimization. In: Proc. MICCAI, pp. 860-868.
17. Donner, R., Birngruber, E., Steiner, H., Bischof, H., Langs, G., 2010a. Localization of 3D anatomical structures using random forests and discrete optimization. In: Proc. MICCAI Workshop on Medical Computer Vision, pp. 86-95.
18. Donner R., Langs G., Micusik B., Bischof H. Generalized sparse MRF appearance models. Image and Vision Computing 2010, 28:1031-1038.
19. Fakhrai N., Widhalm P., Chiari C., Weber M., Donner R., Langs G., Peloschek P. Automatic assessment of the knee alignment angle on full-limb radiographs. European Journal of Radiology 2010, 74:236-240.
20. Fischl B., Salat D., Busa E., Albert M., Dieterich M., Haselgrove C., van der Kouwe A., Killiany R., Kennedy D., Klaveness S., et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002, 33:341-355.
21. Gall, J., Lempitsky, V., 2009. Class-specific Hough Forests for object detection. In: Proc. CVPR, pp. 1022-1029.
22. Geurts P., Ernst D., Wehenkel L. Extremely randomized trees. Machine Learning 2006, 63:3-42.
23. Grady L. Random walks for image segmentation. TPAMI 2006, 28:1768-1783.
24. Issa, S., Dunlop, D., Chang, A., Song, J., Prasad, P., Guermazi, A., Peterfy, C., Cahue, S., Kapoor, M.M., Hayes, K., Sharma, L., 2007. Full-limb and knee radiography assessments of varus-valgus alignment and their relationship to osteoarthritis disease features by magnetic resonance imaging. Arthritis Rheum 57, 398-406.
25. Kelm, B.M., Zhou, S.K., Suehling, M., Zheng, Y., Wels, M., Comaniciu, D., 2010. Detection of 3D spinal geometry using iterated marginal space learning. In: Proc. MICCAI Workshop on Medical Computer Vision, pp. 96-105.
26. Lamarre M.E., Parent S., Labelle H., Aubin C.E., Cabral J.J.A., Petit Y. Assessment of spinal flexibility in adolescent idiopathic scoliosis: suspension versus side-bending radiography. Spine 2009, 34:591-597.
27. Langs G., Peloschek P., Bischof H., Kainberger F. Automatic quantification of joint space narrowing and erosions in rheumatoid arthritis. IEEE TMI 2009, 28:151-164.
28. Lepetit V., Fua P. Keypoint recognition using randomized trees. TPAMI 2006, 28:1465-1479.
29. Mallinckrodt Institute of Radiology Washington University School of Medicine, 2010. Whole body morphometry project. <>. http://www.nrg.wustl.edu.
30. Menze, B., Kelm, B.M., DN, D.N.S., Koethe, U., Hamprecht, F., 2011. On oblique random forests. In: Proc. of ECML, pp. 453-469.
31. Mičušík, B., Pajdla, T., 2007. Multi-label image segmentation via max-sum solver. In: Proc. CVPR, pp. 1-6.
32. Montillo, A., Shotton, J., Winn, J., Iglesias, J.E., Metaxas, D., Criminisi, A., 2011. Entangled decision forests and their application for semantic segmentation of CT images. In: Proc. IPMI, pp. 184-196.
33. Pauly, O., Glocker, B., Criminisi, A., Mateus, D., Möller, A.M., Nekolla, S., Navab, N., 2011. Fast multiple organ detection and localization in whole-body MR Dixon sequences. In: Proc. MICCAI, pp. 239-247.
34. Peloschek P., Langs G., Weber M., Sailer J., Reisegger M., Imhof H., Bischof H., Kainberger F. An automatic model-based system for joint space measurements on hand radiographs - initial experience. Radiology 2007, 245:855-862.
35. Roberts M., Cootes T.F., Adams J.E. Vertebral morphometry - semiautomatic determination of detailed shape from dual-energy X-ray absorptiometry images using active appearance models. Investigative Radiology 2006, 41:459-849.
36. Schmidt, S., Kappes, J., Bergtholdt, M., Pekar, V., Dries, S., Bystrov, D., Schnörr, C., 2007. Spine detection and labeling using a parts-based graphical model. In: Proc. IPMI, pp. 122-133.
37. Seifert, S., Barbu, A., Zhou, S., Liu, D., Feulner, J., Huber, M., Suehling, M., Cavallaro, A., Comaniciu, D., 2009. Hierarchical parsing and semantic navigation of full body CT data. In: SPIE Proceedings.
38. Sharp, T., 2008. Implementing decision trees and forests on a GPU. In: Forsyth, D., Torr, P., Zisserman, A. (Eds.), Proc. ECCV, pp. 595-608.
39. Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moorea, R., Kipman, A., Blake, A., 2011. Real-time human pose recognition in parts from a single depth image. In: Proc. CVPR, pp. 1297-1304.
40. Tu Z., Bai X. Auto-context and its application to high-level vision tasks and 3D brain image segmentation. TPAMI 2010, 32:1744-1757.
41. Wainwright M.J., Jordan M.I. Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning 2008, 1:1-305.
42. Zheng, Y., Georgescu, B., Comaniciu, D., 2009. Marginal space learning for efficient detection of 2D/3D anatomical structures in medical images. In: Proc. IPMI, pp. 411-422.
43. Zhou X., Wang S., Chen H., Hara T., Yokoyama R., Kanematsu M., Fujita H. Automatic localization of solid organs on 3D CT images by a collaborative majority voting decision based on ensemble learning. Computerized Medical Imaging and Graphics 2012, 10.1016/j.compmedimag.2011.12.004.