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Pattern Recognition and Image Analysis

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01-10-2020 | APPLIED PROBLEMS

Automatic Segmentation and Analysis of Renal Calculi in Medical Ultrasound Images

Authors: Prema T. Akkasaligar, Sunanda Biradar

Published in: Pattern Recognition and Image Analysis | Issue 4/2020

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Abstract

Ultrasonography images have a high impact in the medical field for faster and accurate diagnosis of the diseases. The analysis and processing of ultrasound images is a tedious task. The proposed work focuses on automatic segmentation and analysis of renal calculi in digital ultrasound kidney images. The developed methodology includes steps such as preprocessing, segmentation and analysis. Preprocessing includes despeckling of input ultrasound images and is performed by using contourlet transform. Preprocessed images undergo automatic segmentation using the level set method. Analysis of the segmented stones is also carried out to obtain metrics such as the number of stones and their sizes. These metrics are essential to decide about the further plan of treatment by urologists and nephrologists. Performance of the developed algorithm is evaluated by the medical experts and also by using the various parameters such as dice similarity coefficient, Jaccard index, specificity, sensitivity, and accuracy.

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Title: Automatic Segmentation and Analysis of Renal Calculi in Medical Ultrasound Images
Authors: Prema T. Akkasaligar
Sunanda Biradar
Publication date: 01-10-2020
Publisher: Pleiades Publishing
Published in: Pattern Recognition and Image Analysis / Issue 4/2020
Print ISSN: 1054-6618
Electronic ISSN: 1555-6212
DOI: https://doi.org/10.1134/S1054661820040021

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