Fast Segmentation for Texture-based Cartography of whole Slide Images

Grégory Apou, Benoît Naegel, Germain Forestier, Friedrich Feuerhake, Cédric Wemmert

Abstract

In recent years, new optical microscopes have been developed, providing very high spatial resolution images called Whole Slide Images (WSI). The fast and accurate display of such images for visual analysis by pathologists and the conventional automated analysis remain challenging, mainly due to the image size (sometimes billions of pixels) and the need to analyze certain image features at high resolution. To propose a decision support tool to help the pathologist interpret the information contained by the WSI, we present a new approach to establish an automatic cartography of WSI in reasonable time. The method is based on an original segmentation algorithm and on a supervised multiclass classification using a textural characterization of the regions computed by the segmentation. Application to breast cancer WSI shows promising results in terms of speed and quality.

References

  1. Elston, C. W. and Ellis, I. O. (1991). Pathological prognostic factors in breast cancer. i. the value of histological grade in breast cancer: Experience from a large study with long-term follow-up. Histopathology.
  2. Fawcett, T. (2006). An introduction to roc analysis. Pattern Recognition Letters.
  3. Ghaznavi, F., Evans, A., Madabhushi, A., and Feldman, M. (2013). Digital imaging in pathology: Whole-slide imaging and beyond. Annual Review of Pathology.
  4. Gurcan, M. N., Boucheron, L. E., Can, A., Madabhushi, A., Rajpoot, N. M., and Yener, B. (2009). Histopathological image analysis: a review. IEEE Reviews in Biomedical Engineering.
  5. Homeyer, A., Schenk, A., Arlt, J., Dahmen, U., Dirsch, O., and Hahn, H. K. (2013). Practical quantification of necrosis in histological whole-slide images. Computerized Medical Imaging and Graphics.
  6. Huang, C.-H., Veillard, A., Roux, L., Loménie, N., and Racoceanu, D. (2010). Time-efficient sparse analysis of histopathological whole slide images. Computerized Medical Imaging and Graphics.
  7. Montanari, U. (1971). On the optimal detection of curves in noisy pictures. Communications of the ACM.
  8. Ojala, T., Pietikäinen, M., and Harwood, D. (1996). A comparative study of texture measures with classification based on featured distributions. Pattern Recognition.
  9. Roullier, V., Lézoray, O., Ta, V.-T., and Elmoataz, A. (2011). Multi-resolution graph-based analysis of histopathological whole slide images: application to mitotic cell extraction and visualization. Computerized Medical Imaging and Graphics.
  10. Ruiz, A., Sertel, O., Ujaldon, M., Catalyurek, U., Saltz, J., and Gurcan, M. (2007). Pathological image analysis using the gpu: Stroma classification for neuroblastoma. 2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007).
  11. Sertel, O., Kong, J., Shimada, H., and Catalyurek, U. (2009). Computer-aided prognosis of neuroblastoma on whole-slide images: Classification of stromal development. Pattern Recognition.
  12. Signolle, N., Plancoulaine, B., Herlin, P., and Revenu, M. (2008). Texture-based multiscale segmentation: Application to stromal compartment characterization on ovarian carcinoma virtual slides. Image and Signal Processing.
  13. Tavassoli, F. A. and Devilee, P. (2003). Pathology and Genetics of Tumours of the Breast and Female Genital Organs. IARCPress.
  14. Wemmert, C., Krüger, J., Forestier, G., Sternberger, L., Feuerhake, F., and Ganc¸arski, P. (2013). Stain unmixing in brightfield multiplexed immunohistochemistry. IEEE International Conference on Image Processing.
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Paper Citation


in Harvard Style

Apou G., Naegel B., Forestier G., Feuerhake F. and Wemmert C. (2014). Fast Segmentation for Texture-based Cartography of whole Slide Images . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 309-319. DOI: 10.5220/0004687403090319


in Bibtex Style

@conference{visapp14,
author={Grégory Apou and Benoît Naegel and Germain Forestier and Friedrich Feuerhake and Cédric Wemmert},
title={Fast Segmentation for Texture-based Cartography of whole Slide Images},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={309-319},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004687403090319},
isbn={978-989-758-003-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Fast Segmentation for Texture-based Cartography of whole Slide Images
SN - 978-989-758-003-1
AU - Apou G.
AU - Naegel B.
AU - Forestier G.
AU - Feuerhake F.
AU - Wemmert C.
PY - 2014
SP - 309
EP - 319
DO - 10.5220/0004687403090319