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Multiscale Detection of Cancerous Tissue in High Resolution Slide Scans

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Advances in Visual Computing (ISVC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12510))

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Abstract

We present an algorithm for multi-scale tumor (chimeric cell) detection in high resolution slide scans. The broad range of tumor sizes in our dataset pose a challenge for current Convolutional Neural Networks (CNN) which often fail when image features are very small (8 pixels). Our approach modifies the effective receptive field at different layers in a CNN so that objects with a broad range of varying scales can be detected in a single forward pass. We define rules for computing adaptive prior anchor boxes which we show are solvable under the equal proportion interval principle. Two mechanisms in our CNN architecture alleviate the effects of non-discriminative features prevalent in our data - a foveal detection algorithm that incorporates a cascade residual-inception module and a deconvolution module with additional context information. When integrated into a Single Shot MultiBox Detector (SSD), these additions permit more accurate detection of small-scale objects. The results permit efficient real-time analysis of medical images in pathology and related biomedical research fields.

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Acknowledgements

We thank K08 DK085141 and the American Cancer Society Chris DiMarco Institutional Research Grant (CDH) for funding support. This work was conducted at the UF Graphics Imaging and Light Measurement Lab (GILMLab).

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Authors and Affiliations

  1. University of Florida, Gainesville, FL, 32611, USA

    Qingchao Zhang, Coy D. Heldermon & Corey Toler-Franklin

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  1. Qingchao Zhang
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  2. Coy D. Heldermon
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  3. Corey Toler-Franklin
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Corresponding author

Correspondence to Corey Toler-Franklin .

Editor information

Editors and Affiliations

  1. University of Nevada Reno, Reno, NV, USA

    George Bebis

  2. Stony Brook University, Stony Brook, NY, USA

    Zhaozheng Yin

  3. Drexel University, Philadelphia, PA, USA

    Edward Kim

  4. RWTH Aachen University, Aachen, Germany

    Jan Bender

  5. University of Edinburgh, Edinburgh, UK

    Kartic Subr

  6. IBM Research – Cambridge, Cambridge, MA, USA

    Bum Chul Kwon

  7. University of Waterloo, Waterloo, ON, Canada

    Jian Zhao

  8. Graz University of Technology, Graz, Austria

    Denis Kalkofen

  9. The Hong Kong Polytechnic University, Hong Kong, Hong Kong

    George Baciu

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Zhang, Q., Heldermon, C.D., Toler-Franklin, C. (2020). Multiscale Detection of Cancerous Tissue in High Resolution Slide Scans. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science(), vol 12510. Springer, Cham. https://doi.org/10.1007/978-3-030-64559-5_11

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  • DOI: https://doi.org/10.1007/978-3-030-64559-5_11

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  • Online ISBN: 978-3-030-64559-5

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