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Cancer Diagnosis and Prognosis Assistance Based on MCA

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Multidisciplinary Computational Anatomy

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Abstract

We are developing a detection/diagnosis system for lung cancer and chest diseases. These research use synchrotron radiation large-field microscopic CT images, high-definition CT images and pathology/clinical information, and long-term low-dose CT images and genetic information. We present high-performance computer-aided diagnosis system by analyzing the pathological condition from these multiscale image information. These results are described.

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Acknowledgments

This research was supported by JSPS Kakenhi 26108007. We would like to express our deep gratitude to all our collaborators.

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Authors and Affiliations

  1. Emeritus Professor, Tokushima University, Tokushima, Japan

    Noboru Niki

  2. Division of Science and Technology, Graduate School of Technology, Industrial and Social Sciences, Tokushima University, Tokushima, Japan

    Yoshiki Kawata, Hidenobu Suzuki & Mikio Matsuhiro

  3. Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan

    Kurumi Saito

Authors
  1. Noboru Niki
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  2. Yoshiki Kawata
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  3. Hidenobu Suzuki
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  4. Mikio Matsuhiro
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  5. Kurumi Saito
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Corresponding author

Correspondence to Noboru Niki .

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Editors and Affiliations

  1. Professor Emeritus, Kyushu University, Fukuoka, Japan

    Makoto Hashizume

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Niki, N., Kawata, Y., Suzuki, H., Matsuhiro, M., Saito, K. (2022). Cancer Diagnosis and Prognosis Assistance Based on MCA. In: Hashizume, M. (eds) Multidisciplinary Computational Anatomy. Springer, Singapore. https://doi.org/10.1007/978-981-16-4325-5_7

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  • DOI: https://doi.org/10.1007/978-981-16-4325-5_7

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