Research of textural features for the diagnostics of nephrological diseases using ultrasound images

Abstract

A method of automated diagnostics of kidney diseases using ultrasound images is proposed. The efficiency of different groups of information features of such images for the task of recognition is analyzed. According to the data of a number of experiments on real data the group of two Haralick’s features showed the best result. The estimation of probability of wrong recognition for that group was 0.06. Spectral correlation features also demonstated high efficiency, the estimation of the latter for them being 0.10.

About the authors

A. V. Gaidel

Samara State Aerospace University

Author for correspondence.
Email: andrey.gaidel@gmail.com

Postgraduate student

Technical Cybernetics Department

Russian Federation

S. N. Larionova

Samara State Medical University

Email: larionovasn@gmail.com

Senior Laboratory Assistant

Department of Operative Surgery and Clinical Anatomy with a Course on Innovation Technologies

Russian Federation

A. G. Khramov

Samara State Aerospace University

Email: khramov@smr.ru

Doctor of Science (Engineering), Professor

Technical Cybernetics Department

Russian Federation

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