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Cell Detection with Deep Learning Accelerated by Sparse Kernel

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Deep Learning and Convolutional Neural Networks for Medical Image Computing

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

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Abstract

As lung cancer is one of the most frequent and serious disease causing death for both men and women, early diagnosis and differentiation of lung cancers is clinically important. Computerized tissue histopathology image analysis and computer-aided diagnosis is very efficient and has become amenable. The cell detection process is the most basic step among the computer-aided histopathology image analysis applications. In this chapter, we study a deep convolutional neural network-based method for the lung cancer cell detection problem. This problem is very challenging due to many reasons, e.g., cell clumping and overlapping, high complexity of the cell detection methods, and the lack of humanly annotated datasets. To address these issues, we introduce a deep learning-based cell detection method for the effectiveness, as the deep learning methods have been demonstrated to be repeatedly successful in various computer vision applications in the last decade. However, this method still takes very long time to detect cells in very small images, e.g., \(512\times 512\), albeit it is very effective in the cell detection task. In order to reduce the overall time cost of this method, we combine this method with the sparse kernel technique to significantly accelerate the cell detection process, up to 500 times. With the aforementioned advances, our numerical results confirm that the resulting method is able to outperform most state-of-the-art cell detection methods in terms of both efficiency and effectiveness.

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Authors and Affiliations

  1. University of Texas at Arlington, 701 S. Nedderman Dr., Arlington, TX, 76013, USA

    Junzhou Huang & Zheng Xu

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  1. Junzhou Huang
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  2. Zheng Xu
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Correspondence to Junzhou Huang .

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Editors and Affiliations

  1. NIH Clinical Center, Bethesda, Maryland, USA

    Le Lu

  2. Siemens Healthcare Technology Center, Princeton, New Jersey, USA

    Yefeng Zheng

  3. University of Adelaide, Adelaide, South Australia, Australia

    Gustavo Carneiro

  4. University of Florida, Gainesville, Florida, USA

    Lin Yang

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Huang, J., Xu, Z. (2017). Cell Detection with Deep Learning Accelerated by Sparse Kernel. In: Lu, L., Zheng, Y., Carneiro, G., Yang, L. (eds) Deep Learning and Convolutional Neural Networks for Medical Image Computing. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-42999-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-42999-1_9

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  • Online ISBN: 978-3-319-42999-1

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