A computational model for medical image retrieval using orthogonal moment

This Paper Deals With Image Retrieval Process Of Liver Computer Tomography (Ct) Scan Images Using Orthogonal Moment Features And Content Based Image Retrieval. Medical Images Are Useful Diagnostic Evidence As It Can Provide Vital Information In Anatomical Pathology. The Objective Is To Efficiently R...

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Bibliographic Details
Published in:Journal of intelligent & fuzzy systems 2023-01, Vol.44 (2), p.3261
Main Authors: Nallasivan, G, Akshaya, V S, Padmavathy, C
Format: Article
Language:English
Subjects:
Computed tomography
Feature extraction
Image segmentation
Medical imaging
Polynomials
Retrieval
Online Access:Get full text
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Summary:This Paper Deals With Image Retrieval Process Of Liver Computer Tomography (Ct) Scan Images Using Orthogonal Moment Features And Content Based Image Retrieval. Medical Images Are Useful Diagnostic Evidence As It Can Provide Vital Information In Anatomical Pathology. The Objective Is To Efficiently Retrieve Medical Images From The Database Using Orthogonal Moments And Content Based Image Retrieval Methods. The Orthogonal Moment Viz Discrete Racah Polynomial, Continuous Legendre Moments And Zernike Moments Are Computed For The Study. The Region Of Interest Based Segmentation And Watershed Segmentation Is Applied To The Preprocessed Input Images And Features Are Extracted Using Orthogonal Moments And Shape And Texture Features Are Extracted Using Content Based Image Retrieval (Cbir). The Performances Of Each Moment In Terms Of Accuracy And Error Rate Are Compared With Cbir.
ISSN:1064-1246
1875-8967
DOI:10.3233/JIFS-221667