Mass detection in mammography using texture analysis

Shu-Mei Guo, Ping Sung Liao, Yu Chian Liao, Sheng Chih Yang, Pau-Choo Chung, San Kan Lee, Chein I. Chang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this article, feature selection based on the texture spectrum and texture feature coding method is considered to depict the characteristics of mass in mammograms for mass detection. It is quite unlike that of either the features of gray level histogram or the features of spatial gray level dependence that were often chosen as the feature vector of the mass in the past. The texture spectrum fully represents the first-order gray level change of a pixel in a texture unit (a cell composed by a center pixel and its eight connected pixels); meanwhile texture feature coding method emphasizes the second-order gray level change in the horizontal and vertical direction of a pixel in a texture unit. For the purpose of mass detection, both can capture the subtle of gray level change better than the conventional methods of gray level histogram and spatial gray level dependence. Experimental results evidently show that our proposed texture based feature vector can get better diagnostic judgment in mass detection and mass classification. It is worthy of note that texture analysis is recommended as important parameters in mass detection and mass classification in the computer-aided detection of mammograms.

Original languageEnglish
Pages (from-to)149-157
Number of pages9
JournalChinese Journal of Radiology
Volume28
Issue number3
Publication statusPublished - 2003 Jan 1

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Guo, S-M., Liao, P. S., Liao, Y. C., Yang, S. C., Chung, P-C., Lee, S. K., & Chang, C. I. (2003). Mass detection in mammography using texture analysis. Chinese Journal of Radiology, 28(3), 149-157.