Statistical interpretation of texture for medical applications

A. Glen Houston; Saganti B. Premkumar; David E. Pitts; Richard J. Babaian

doi:10.1117/12.59586

26 June 1992 Statistical interpretation of texture for medical applications

A. Glen Houston, Saganti B. Premkumar, David E. Pitts, Richard J. Babaian

Proceedings Volume 1660, Biomedical Image Processing and Three-Dimensional Microscopy; (1992) https://doi.org/10.1117/12.59586
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States

Abstract

Findings from transrectal ultrasound examinations of the prostate are usually based on the echogenicity observed by visual interpretation of the ultrasound image. Hypoechoic areas are typically suspected to be cancerous. Previous studies have indicated that a high percentage (as high as 96%) of cancerous lesions are hypoechoic, but only a moderate percentage (about 50%) of hypoechoic regions are cancerous. We have been investigating statistical measures of texture of digitized ultrasound images of the prostate to assess whether improved accuracies can be achieved for diagnosing prostate cancer and for identifying cancerous lesions. This paper presents our approach as well as results obtained for 17 patients, eight non-cancerous and nine cancerous. The results of a small `blind test,' based on seven subjects, are also presented. Recently, a pathological mount of a prostate cross-section from a prostatectomy was selected as a test case for applying texture analysis to detect prostatic adenocarcinoma. The approach and results are described. The results of both studies are encouraging, but must be considered exploratory due to the small data sets. The results do provide support to the idea that texture information in the prostate is related to a structural change in the gland when carcinoma occurs.

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A. Glen Houston, Saganti B. Premkumar, David E. Pitts, and Richard J. Babaian "Statistical interpretation of texture for medical applications", Proc. SPIE 1660, Biomedical Image Processing and Three-Dimensional Microscopy, (26 June 1992); https://doi.org/10.1117/12.59586

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