Tissue characterization by texture analysis of ultrasonic images

Olivier Basset; Zhigang Sun; Gerard Gimenez

doi:10.1117/12.139102

12 January 1993 Tissue characterization by texture analysis of ultrasonic images

Olivier Basset, Zhigang Sun, Gerard Gimenez

Author Affiliations +

Proceedings Volume 1771, Applications of Digital Image Processing XV; (1993) https://doi.org/10.1117/12.139102
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

Ultrasonic B-scan images present a particular texture known as "speckle" which may reveal information relative to the investigated tissue structure. The present work is devoted to the discrimination of various prostatic tissues (normal tissue, benign prostatic hypertrophy and cancer). This is done on ultrasonic scans by means of texture analysis. Three methods have been implemented: the autocorrelation function and the co-occurrence matrices, measuring second order statistics and the grey level run lengths matrices. Parameters derived from the co-occurence matrices provides a fairly good tissue signature. The processing of 37 images gives a 78% score of samples classified with success. Note that the various images can not be visually discriminated. However, such results are obtained when wide regions of interest are investigated (64 x 64 pixels), but they are less significant when the sample size decreases, that is when the pathological area is very small.

Citation Download Citation

Olivier Basset, Zhigang Sun, and Gerard Gimenez "Tissue characterization by texture analysis of ultrasonic images", Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); https://doi.org/10.1117/12.139102

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