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2018 年度 実績報告書

Automatic Detection of Good/Bad Colonies of iPS Cells Using Deep Learning

研究課題

研究課題/領域番号 16K00394
研究機関広島大学

研究代表者

ライチェフ ビセル  広島大学, 工学研究科, 准教授 (00531922)

研究期間 (年度) 2016-04-01 – 2019-03-31
キーワードiPS cells / Machine learning / Neural networks
研究実績の概要

Induced pluripotent stem (iPS) cells have shown a huge potential for the development of regenerative medicine. However, since a large number of undifferentiated human iPS cells must be prepared for use as a renewable source of replacement cells for regenerative medicine, the development of an automated culture system for iPS cells is considered very important. In such a system, detecting the anomalies which can arise during the culture process is considered to be crucial. In this research project we have designed a novel machine learning based method for automatic detection of Good (undifferentiated) vs. Bad (differentiated) colonies of iPS cells directly from images, which makes possible the automation of the cell harvesting process.

The proposed method is based on deep learning using a Convolutional Neural Network (CNN) with a modified architecture which is better able to capture the relevant structural information regarding the spatial distribution of class probabilities. Additionally, the training can be accomplished using only a small labeled training dataset. Experimental results show that very good accuracy can be achieved by the proposed method, outperforming other current state-of-the-art algorithms for biomedical image analysis.

  • 研究成果

    (4件)

すべて 2018

すべて 学会発表 (4件) (うち国際学会 1件、 招待講演 2件)

  • [学会発表] Patch-based learning for biomedical image analysis2018

    • 著者名/発表者名
      Bisser Raytchev
    • 学会等名
      Hiroshima Conference on Statistical Science 2016
    • 国際学会 / 招待講演
  • [学会発表] Detection of Differentiated vs. Undifferentiated Colonies of iPS Cells Using Random Forests Modeled with the Multivariate Polya Distribution2018

    • 著者名/発表者名
      Bisser Raytchev
    • 学会等名
      第20回 画像の認識・理解シンポジウム(MIRU2017)
    • 招待講演
  • [学会発表] 構造情報を用いた分類型CNNによるiPS細胞の分化・未分化検出2018

    • 著者名/発表者名
      林 祥平, Bisser Raytchev, 玉木 徹, 金田 和文
    • 学会等名
      第21回 画像の認識・理解シンポジウム(MIRU2018)
  • [学会発表] Multi-Scale Scene Recognition Using Small Training Datasets2018

    • 著者名/発表者名
      Tokinirina Radiniaina, Bisser Raytchev, Kazufumi Kaneda, Toru Tamaki
    • 学会等名
      第21回 画像の認識・理解シンポジウム(MIRU2018)

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公開日: 2019-12-27  

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