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[Analysis of scintigrams using fuzzy theory].

H Ikeda1, Y Shimonishi, M Ohmura

  • 1Department of Radiology, Osaka City University Hospital, Japan.

Radioisotopes
|November 1, 1990
PubMed
Summary

This study introduces fuzzy reasoning for analyzing image textural features, overcoming limitations of discriminant analysis. Fuzzy reasoning offers a more suitable method for analyzing clinical scintigrams.

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Area of Science:

  • Medical imaging analysis
  • Image texture analysis
  • Fuzzy logic applications

Background:

  • Texture parameters like skew, energy, entropy, and angular second moment were extracted from phantom images.
  • Discriminant analysis proved difficult for analyzing textural features due to statistical noise.

Purpose of the Study:

  • To adapt fuzzy reasoning for analyzing image textural features.
  • To evaluate the suitability of fuzzy reasoning compared to discriminant analysis for image analysis.

Main Methods:

  • Extracted textural features (skew, energy, entropy, angular second moment) from phantom images.
  • Applied fuzzy reasoning using membership functions and max-min composition for image analysis.
  • Compared fuzzy reasoning with discriminant analysis.

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Main Results:

  • Fuzzy reasoning successfully analyzed textural features from six types of images.
  • The possibility of an image was evaluated using membership function values.
  • Fuzzy reasoning demonstrated greater suitability than discriminant analysis for image analysis.

Conclusions:

  • Fuzzy reasoning is a more suitable method than discriminant analysis for analyzing image textural features.
  • This approach shows promise for the analysis of clinical scintigrams.