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Medical & Biological Engineering & Computing
Published in: Medical & Biological Engineering & Computing 7-8/2021

26-06-2021 | Original Article

Ventricle shape analysis using modified WKS for atrophy detection

Authors: Jayaraman Thirumagal, Manjunatha Mahadevappa, Anup Sadhu, Pranab Kumar Dutta

Published in: Medical & Biological Engineering & Computing | Issue 7-8/2021

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Abstract

Brain ventricle is one of the biomarkers for detecting neurological disorders. Studying the shape of the ventricles will aid in the diagnosis process of atrophy and other CSF-related neurological disorders, as ventricles are filled with CSF. This paper introduces a spectral analysis algorithm based on wave kernel signature. This shape signature was used for studying the shape of segmented ventricles from the brain images. Based on the shape signature, the study groups were classified as normal subjects and atrophy subjects. The proposed algorithm is simple, effective, automated, and less time consuming. The proposed method performed better than the other methods heat kernel signature, scale invariant heat kernel signature, wave kernel signature, and spectral graph wavelet signature, which were used for validation purpose, by producing 94–95% classification accuracy by classifying normal and atrophy subjects correctly for CT, MR, and OASIS datasets.

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Metadata
Title
Ventricle shape analysis using modified WKS for atrophy detection
Authors
Jayaraman Thirumagal
Manjunatha Mahadevappa
Anup Sadhu
Pranab Kumar Dutta
Publication date
26-06-2021
Publisher
Springer Berlin Heidelberg
Published in
Medical & Biological Engineering & Computing / Issue 7-8/2021
Print ISSN: 0140-0118
Electronic ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-021-02377-z

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