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Automated Analysis of PIN-4 Stained Prostate Needle Biopsies

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Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention (Prostate Cancer Imaging 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6367))

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Abstract

Prostate Needle biopsies are stained with the PIN-4 marker cocktail to help the pathologist distinguish between HGPIN and adenocarcinoma. The correct interpretation of multiple IHC markers can be challenging. Therefore we propose the use of computer aided diagnosis algorithms for the identification and classification of glands in a whole slide image of prostate needle biopsy. The paper presents the different issues related to the automated analysis of prostate needle biopsies and the approach taken by BioImagene in its first generation algorithms.

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References

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Author information

Authors and Affiliations

  1. BioImagene Inc., 919 Hermosa Court, Sunnyvale, CA, 94085

    Bikash Sabata, Boris Babenko, Robert Monroe & Chukka Srinivas

Authors
  1. Bikash Sabata
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  2. Boris Babenko
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  3. Robert Monroe
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  4. Chukka Srinivas
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Editor information

Editors and Affiliations

  1. Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, 08854, Piscataway, NJ, USA

    Anant Madabhushi

  2. CSIRO Australian e-Health Research Centre, Royal Brisbane and Women’s Hospital, 4029, Herston, QLD, Australia

    Jason Dowling

  3. Philips Research North America, 345 Scarborough Road, 10510, Briarcliff Manor, NY, USA

    Pingkun Yan

  4. Imaging Research Laboratories, Robarts Research Institute, 100 Perth Drive, N6A 5K8, London, Ontario, Canada

    Aaron Fenster

  5. Department of Electrical and Computer Engineering, University of British Columbia, 2332 Main Mall, V6T 1Z4, Vancouver, BC, Canada

    Purang Abolmaesumi

  6. Brigham and Women’s Hospital and Harvard Medical School, 75 Francis, 02115, St., Boston, MA, USA

    Nobuhiko Hata

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© 2010 Springer-Verlag Berlin Heidelberg

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Sabata, B., Babenko, B., Monroe, R., Srinivas, C. (2010). Automated Analysis of PIN-4 Stained Prostate Needle Biopsies. In: Madabhushi, A., Dowling, J., Yan, P., Fenster, A., Abolmaesumi, P., Hata, N. (eds) Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention. Prostate Cancer Imaging 2010. Lecture Notes in Computer Science, vol 6367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15989-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-15989-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15988-6

  • Online ISBN: 978-3-642-15989-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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