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Diagnosis of Prostate Cancer with Support Vector Machine Using Multiwavelength Photoacoustic Images

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Proceedings of 3rd International Conference on Computer Vision and Image Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1022))

Abstract

Photoacoustic (PA) imaging is an emerging soft tissue imaging modality which can be potentially used for the detection of prostate cancer. Computer-aided diagnosis tools help in further enhancing the detection process by assisting the physiologist in the interpretation of medical data. In this study, we aim to classify the malignant and nonmalignant prostate tissue using a support vector machine algorithm applied to the multiwavelength PA data obtained from human patients. The performance comparison between two feature sets, one consisting of multiwavelength PA image pixel values and the other consisting of chromophore concentration values are reported. While chromophore concentration values detected malignant prostate cancer more efficiently, the PA image pixels detected the nonmalignant prostate specimens with higher accuracy. This study shows that multiwavelength PA image data can be efficiently used with the support vector machine algorithm for prostate cancer detection.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, India

    Aniket Borkar, Saugata Sinha & Nikhil Dhengre

  2. Department of Imaging Science, University of Rochester Medical Center, Rochester, USA

    Bhargava Chinni, Vikram Dogra & Navalgund Rao

Authors
  1. Aniket Borkar
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  2. Saugata Sinha
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  3. Nikhil Dhengre
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  4. Bhargava Chinni
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  5. Vikram Dogra
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  6. Navalgund Rao
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Corresponding author

Correspondence to Aniket Borkar .

Editor information

Editors and Affiliations

  1. Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India

    Bidyut B. Chaudhuri

  2. Department of Advanced Information Technology and Computer Sciences, Tokyo Institute of Agriculture and Technology, Koganei, Tokyo, Japan

    Masaki Nakagawa

  3. Department of Computer Science, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, Jabalpur, Madhya Pradesh, India

    Pritee Khanna

  4. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Sanjeev Kumar

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Borkar, A., Sinha, S., Dhengre, N., Chinni, B., Dogra, V., Rao, N. (2020). Diagnosis of Prostate Cancer with Support Vector Machine Using Multiwavelength Photoacoustic Images. In: Chaudhuri, B., Nakagawa, M., Khanna, P., Kumar, S. (eds) Proceedings of 3rd International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1022. Springer, Singapore. https://doi.org/10.1007/978-981-32-9088-4_21

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  • DOI: https://doi.org/10.1007/978-981-32-9088-4_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9087-7

  • Online ISBN: 978-981-32-9088-4

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