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Pattern Recognition and Image Analysis
Erschienen in: Pattern Recognition and Image Analysis 4/2020

01.10.2020 | APPLIED PROBLEMS

Automatic Segmentation and Analysis of Renal Calculi in Medical Ultrasound Images

verfasst von: Prema T. Akkasaligar, Sunanda Biradar

Erschienen in: Pattern Recognition and Image Analysis | Ausgabe 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.
Vorheriger Artikel Foundations of Creation of a Complex of Applied Intelligent Systems for Diagnostics of Psychological Safety and Cognitive Sphere of Patients with a Neurological Pathology
Nächster Artikel Wrapper Filter Approach for Accelerometer-Based Human Activity Recognition

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Metadaten
Titel
Automatic Segmentation and Analysis of Renal Calculi in Medical Ultrasound Images
verfasst von
Prema T. Akkasaligar
Sunanda Biradar
Publikationsdatum
01.10.2020
Verlag
Pleiades Publishing
Erschienen in
Pattern Recognition and Image Analysis / Ausgabe 4/2020
Print ISSN: 1054-6618
Elektronische ISSN: 1555-6212
DOI
https://doi.org/10.1134/S1054661820040021

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