A computer-aided system for mass detection and classification in digitized mammograms

Sheng Chih Yang, Chuin Mu Wang, Yi Nung Chung, Giu Cheng Hsu, San Kan Lee, Pau Choo Chung, Chein I. Chang

Research output: Contribution to journalReview articlepeer-review

44 Citations (Scopus)


This paper presents a computer-assisted diagnostic system for mass detection and classification, which performs mass detection on regions of interest followed by the benign-malignant classification on detected masses. In order for mass detection to be effective, a sequence of preprocessing steps are designed to enhance the intensity of a region of interest, remove the noise effects and locate suspicious masses using five texture features generated from the spatial gray level difference matrix (SGLDM) and fractal dimension. Finally, a probabilistic neural network (PNN) coupled with entropic thresholding techniques is developed for mass extraction. Since the shapes of masses are crucial in classification between benignancy and malignancy, four shape features are further generated and joined with the five features previously used in mass detection to be implemented in another PNN for mass classification. To evaluate our designed system a data set collected in the Taichung Veteran General Hospital, Taiwan, R.O.C. was used for performance evaluation. The results are encouraging and have shown promise of our system.

Original languageEnglish
Pages (from-to)215-228
Number of pages14
JournalBiomedical Engineering - Applications, Basis and Communications
Issue number5
Publication statusPublished - 2005 Oct 25

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Bioengineering
  • Biomedical Engineering


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