A computational model for medical image retrieval using orthogonal moment

Autor:	G. Nallasivan, V.S. Akshaya, C. Padmavathy
Rok vydání:	2023
Předmět:	Statistics and Probability Artificial Intelligence General Engineering
Zdroj:	Journal of Intelligent & Fuzzy Systems. 44:3261-3269
ISSN:	1875-8967 1064-1246
DOI:	10.3233/jifs-221667
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ca1d4a35d2ded36a25caf96f034b991c https://doi.org/10.3233/jifs-221667 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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