Automatic Detection of Nuclei Regions from HE-Stained Breast Tumor Images Using Artificial Organisms

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概要

• 論文の詳細を見る

• This paper describes an automatic region segmentation method which is detectable nuclei regions from hematoxylin and eosin(HE)-stained breast tumor images using artificial organisms. In this model, the stained images are treated as virtual environments which consist of nuclei, interstitial tissue and background regions. The movement characteristics of each organism are controlled by the gene and the adaptive behavior of each organism is evaluated by calculating the similarities of the texture features before and after the movement. In the nuclei regions, the artificial organisms can survive, obtain energy and product offspring. Organisms in other regions lose energy by the movement and die during searching. As a result, nuclei regions are detected by the collective behavior of artificial organisms. The method developed was applied to 9 cases of breast tumor images and detection of nuclei regions by the artificial organisms was successful in all cases. The proposed method has the following advantages:(1)the criteria of each organism's texture feature values(supervised values)for the evaluation of nuclei regions are decided automatically at the learning stage in every input image;(2)the proposed algorithm requires only the similarity ratio as the threshold value when each organism evaluates the environment;(3)this model can successfully detect the nuclei regions without affecting the variance of color tones in stained images which depends on the tissue condition and the degree of malignancy in each breast tumor case.

• 社団法人電子情報通信学会の論文
• 1998-04-25

著者

• Fujisawa Yasunori

  Clinical Laboratory Muroran City General Hospital

• UOZUMI Takashi

  Faculty of Technology, Muroran Institute of Technology

• ONO Koichi

  Faculty of Technology, Muroran Institute of Technology

• Ono K

  Muroran Inst. Technol. Muroran‐shi Jpn

• Okii H

  Muroran Inst. Technol. Muroran‐shi Jpn

• Uozumi T

  Muroran Inst. Technol. Muroran‐shi Jpn

• OKII Hironori

  the Faculty of Technology, Muroran Institute of Technology

• UOZUMI Takashi

  the Faculty of Technology, Muroran Institute of Technology

• ONO Koichi

  the Faculty of Technology, Muroran Institute of Technology

• FUJISAWA Yasunori

  the Clinical Laboratory, Muroran City General Hospital

関連論文

• Automatic Feature Extraction from Breast Tumor Images Using Artificial Organisms
• Electroluminescence in Perylene-and-Tetracene-Doped Anthracene Films
• Electroluminescence in Perylene-Doped Anthracene Films : The Ambient Gas Effect in the Emission Process
• Feature Extraction for Classification of Breast Tumor Images Using Artificial Organisms
• Automatic Detection of Nuclei Regions from HE-Stained Breast Tumor Images Using Artificial Organisms
• Detection of Breast Carcinoma Regions Using Artificial Organisms
• Automatic Color Segmentation Method Using a Neural Network Model for Stained Images

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