Image Quantification and Machine Learning in Cell Biology

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  • 細胞生物学における画像の定量評価と機械学習
  • サイボウ セイブツガク ニ オケル ガゾウ ノ テイリョウ ヒョウカ ト キカイ ガクシュウ

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Abstract

<p>Examination of microscopic images is a fundamental method in cell biology. Traditionally, the use of microscopic images has tended to be limited to qualitative interpretation based on visual inspections. However, this conventional method may lack objectivity, and the human labor cost becomes huge when a large number of image datasets need to be examined. To overcome these problems, we have been developing image analysis frameworks for quantitative evaluation and classification of cell features using machine learning techniques. In this article, we review our work, including a microscopic data mining method based on quantitative evaluation and clustering of cytoskeletal structures, the CARTA framework for versatile biomedical image classification, and a semi-automatic method to detect intracellular structures from wide-area microscopic images. We also discuss the benefits of image analysis and machine learning from the perspective of an experimental biologist.</p>

Journal

  • KENBIKYO

    KENBIKYO 55 (3), 109-113, 2020-12-30

    The Japanese Society of Microscopy

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