Wavelet-based multiscale texture segmentation: Application to stromal compartment characterization on virtual slides

Signal Processing

Volumn 90, Issue 8, 2010, Pages 2412-2422

  Signolle, Nicolas ^a   Revenu, Marinette ^a   Plancoulaine, Benoît ^a   Herlin, Paulette ^a  

^a Centre National de la Recherche Scientifique   (France)

Author keywords

Hidden Markov model; Pairwise classifier combination; Segmentation; Texture; Virtual slides; Wavelets

Indexed keywords

CLASSIFIER COMBINATION; CLASSIFIER SELECTION; COLOR IMAGE SEGMENTATION; HIDDEN MARKOV TREE MODEL; HYPERPARAMETERS; LARGE IMAGES; MAJORITY VOTE; MULTISCALE FRAMEWORK; MULTISCALES; OVARIAN CARCINOMA; PAIRWISE CLASSIFIER COMBINATION; SEGMENTATION; SEGMENTATION RESULTS; TEXTURE SEGMENTATION;

CLASSIFIERS; FEATURE EXTRACTION; HIDDEN MARKOV MODELS; TEXTURES;

IMAGE SEGMENTATION;

EID: 77951204152     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2009.11.008     Document Type: Article

References (41)

1. Rojo M.G., García G.B., Mateos C.P., García J.G., and Vicente M.C. Critical comparison of 31 commercially available digital slide systems in pathology. International Journal of Surgical Pathology 14 4 (October 2006) 205-285
2. Xie X. A review of recent advances in surface defect detection using texture analysis techniques. Electronic Letters on Computer Vision and Image Analysis 7 3 (2008) 1-22
3. Crouse M.S., Nowak R., and Baraniuk R. Wavelet-based statistical signal processing using hidden Markov models. IEEE Transactions on Signal Processing 46 (1998) 886-902
4. Mallat S. A Wavelet Tour of Signal Processing (1999), Academic Press, New York 620pp
5. Choi H., and Baraniuk R. Multiscale image segmentation using wavelet-domain hidden Markov models. IEEE Transactions on Image Processing 10 9 (2001) 1309-1321
6. Hamilton P.W., Bartels P.H., Thompson D., Anderson N.H., Montironi R., and Sloan J.M. Automated location of dysplastic fields in colorectal histology using image texture analysis. The Journal of Pathology 182 1 (May 1997) 68-75
7. Tran K., Elie N., Plancoulaine B., Herlin P., and Coster M. An original approach for quantification of blood vessels on the whole tumour section. Analytical Cellular Pathology 25 2 (2003) 63-75
8. Chantrain C.F., Declerck Y.A., Groshen S., and Mcnamara G. Computerized quantification of tissue vascularization using high-resolution slide scanning of whole tumor sections. The Journal of Histochemistry and Cytochemistry 51 2 (February 2003) 151-158
9. Elie N., Plancoulaine B., Signolle J.-P., and Herlin P. A simple way of quantifying immunostained cell nuclei on the whole histologic section. Cytometry 56A (November 2003) 37-45
10. Mesker W.E., Doekhie F.S., Vrolijk H., Keyzer R., Sloos W.C.R., Morreau H., O'Kelly P.S., de Bock G.H., Tollenaar R.A.E.M., and Tanke H.J. Automated analysis of multiple sections for the detection of occult cells in lymph nodes. Clinical Cancer Research 9 13 (2003) 4826-4834
11. Elie N., Labiche A., Michels J.-J., and Herlin P. Control of low-resolution scanning of ovarian tumor stromal compartment. Image Analysis and Stereology 24 (June 2005) 85-93
12. Gundersen H.J., Bendtsen T.F., Korbo L., Marcussen N., Nyengaard J.R., Pakkenberg B., Sørensen F.B., and Vesterby A. Some new, simple and efficient stereological methods and their use in pathological research and diagnosis. Acta Pathologica, Microbiologica et Immunologica Scandinavica 96 5 (1988) 379-394
13. A.H. Olson, Image analysis using the Aperio ScanScope, Technical Report, Apério Technologies, 2006.
14. M. Mete, X. Xu, C.-Y. Fan, G. Shafirstein, Automatic delineation of malignancy in histopathological head and neck slides, in: MCBBS07, Proceedings of the Fourth Annual MidSouth Computational Biology and Bioinformatics Society: Conference, Computational Frontiers in Biomedicine, vol. 8, Supplément 7 of BMC Bioinformatics, New Orleans, USA, abstract S17, 2007.
15. Mosaliganti K., Pan T., Ridgway R., Sharp R., Cooper L., Gulacy A., Sharma A., Irfanoglu O., Machiraju R., Kurc T., de Bruin A., Wenzel P., Leone G., Saltz J.H., and Huang K. An imaging workflow for characterizing phenotypical change in large histological mouse model datasets. Journal of Biomedical Informatics 41 6 (December 2008) 863-873
16. Signolle N., Plancoulaine B., Herlin P., and Revenu M. Texture-based multiscale segmentation: application to stromal compartment characterization on ovarian carcinoma virtual slides. Third International Conference on Image and Signal Processing of Lecture Notes in Computer Science vol. 5099 (2008), Springer, Berlin 173-182
17. Ficsor L., Varga V.S., Tagscherer A., Tulassay Z., and Molnar B. Automated classification of inflammation in colon histological sections based on digital microscopy and advanced image analysis. Cytometry Part A 73A 3 (March 2008) 230-237
18. Y. He, B. Zhang, J. Li, A new multiresolution classification model based on partitioning of feature space, in: IEEE International Conference on Granular Computing, vol. 3, Beijing, China, 2005, pp. 462-467.
19. Y. Wang, R. Turner, D. Crookes, J. Diamond, P. Hamilton, Investigation of methodologies for the segmentation of squamous epithelium from cervical histological virtual slides, in: IMVIP07, Proceedings of the Seventh International Machine Vision and Image Processing Conference, Maynooth, Ireland, 2007, pp. 83-90.
20. Y. Wang, Computer assisted diagnosis of cervical intraepithelial neoplasia (cin) using histological virtual slides, Ph.D. Thesis, School of Electronics, Electrical Engineering and Computer Science, Queen's University, Belfast, UK, April 2008.
21. Sertel O., Kong J., Shimada H., Çatalyürek Ü.V., Saltz J.H., and Gurcan M.N. Computer-aided prognosis of neuroblastoma on whole-slide images: classification of stromal development. Pattern Recognition 42 6 (2009) 1093-1103 (Digital Image Processing and Pattern Recognition Techniques for the Detection of Cancer)
22. J. Kong, H. Shimada, K.L. Boyer, J.H. Saltz, M.N. Gurcan, A new multi-resolution analysis framework for classifying grade of neuroblastic differentiation, Technical Report, Ohio State University, 2007.
23. J. Kong, O. Sertel, H. Shimada, K.L. Boyer, J.H. Saltz, M.N. Gurcan, Computer-aided grading of neuroblastic differentiation: multi-resolution and multi-classifier approach, in: ICIP07, International Conference on Image Processing, vol. 5, San Antonio, TX, USA, 2007, pp. 525-528.
24. Hastings S., Oster S., Langella S., Kurc T.M., Pan T., Çatalyürek Ü.V., and Saltz J.H. A grid-based image archival and analysis system. Journal of the American Medical Informatics Association 12 3 (May 2005) 286-295
25. Görtler J., Berghoff M., Kayser G., and Kayser K. Grid technology in tissue-based diagnosis: fundamentals and potential developments. Diagnostic Pathology 1 1 (August 2006) 23
26. J.Y. Hong, M.D. Wang, High speed processing of biomedical images using programmable GPU, in: ICIP04: Proceedings of the International Conference on Image Processing, Singapore, 2004, pp. 2455-2458.
27. M. Ujaldon, J.H. Saltz, The GPU on irregular computing: performance issues and contributions, in: CAD-CG05, Proceedings of the Ninth International Conference on Computer Aided Design and Computer Graphics, Hong Kong, 2005, pp. 442-450.
28. O. Sertel, J. Kong, G. Lozanski, A. Shana'ah, Ü.V. Çatalyürek, J.H. Saltz, M.N. Gurcan, Texture classification using nonlinear color quantization: application to histopathological image analysis, in: ICASSP08, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Las Vegas, USA, 2008, pp. 597-600.
29. T.D. Hartley, O. Sertel, M. Khan, Ü.V. Çatalyürek, J.H. Saltz, M.N. Gurcan, Neuroblastoma stroma classification on the Sony PlayStation 3, in: APIII07, The Advancing Practice, Instruction, and Innovation through Informatics Conference on Anatomic Pathology Informatics and Imaging Support for Translational Medicine, Pittsburgh, USA, 2007.
30. Diou C., Torres L., Robert M., and Sassatelli G. Intégration d'une architecture récursive sur silicium pour la transform ée en ondelettes 2D. Traitement du Signal 19 2 (Juillet 2002) 101-117
31. Kong J., Sertel O., Shimada H., Boyer K.L., Saltz J.H., and Gurcan M.N. Computer-aided evaluation of neuroblastoma on whole-slide histology images: classifying grade of neuroblastic differentiation. Pattern Recognition 42 6 (2009) 1080-1092 Digital Image Processing and Pattern Recognition Techniques for the Detection of Cancer
32. A. Renouf, R. Clouard, M. Revenu, How to formulate image processing applications? in: ICCVS07, Proceedings of the International Conference on Computer Vision Systems, Bielefeld, Germany, 2007, p. 10.
33. Deng Y., and Manjunath B. Unsupervised segmentation of color-texture regions in images and video. IEEE Transactions on Pattern Analysis and Machine Intelligence 23 8 (2001) 800-810
34. F. Lecellier, S. Jehan-Besson, J. Fadili, G. Aubert, M. Revenu, E. Saloux, Region-based active contour with noise and shape priors, in: ICIP06, Proceedings of the International Conference on Image Processing, Atlanta, GA, USA, 2006, pp. 1649-1652.
35. Fan G., and Xia X.-G. A joint multicontext and multiscale approach to Bayesian segmentation. IEEE Transactions on Geoscience and Remote Sensing 39 12 (2001) 2680-2688
36. Hastie T., and Tibshirani R. Classification by pairwise coupling. Annals of statistics 26 2 (1998) 451-471
37. J.H. Friedman, Another approach to polychotomous classification, Technical Report, Department of Statistics, Stanford University, 1996.
38. Dietterich T.G., and Bakiri G. Solving multiclass learning problems via error-correcting output codes. Journal of Artificial Intelligence Research 2 (1995) 263-286
39. Allwein E.L., Schapire R.E., and Singer Y. Reducing multiclass to binary: a unifying approach for margin classifiers. Journal of Machine Learning Research 1 (2000) 113-141
40. Scheunders P. An orthogonal wavelet representation of multivalued images. IEEE Transactions on Image Processing 12 6 (2003) 718-725
41. H. Elias, D.M. Hyde, A guide to practical stereology, Karger Continuing Education Series, 1983, 305pp.