IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Application of Content-Based Image Retrieval in Medical Image Acquisition

Application of Content-Based Image Retrieval in Medical Image Acquisition
View Sample PDF
Author(s): Vinayak Majhi (North-Eastern Hill University, India)and Sudip Paul (North-Eastern Hill University, India)
Copyright: 2023
Pages: 17
Source title: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-7544-7.ch022

Purchase

View Application of Content-Based Image Retrieval in Medical Image Acquisition on the publisher's website for pricing and purchasing information.

Abstract

Content-based image retrieval is a promising technique to access visual data. With the huge development of computer storage, networking, and the transmission technology now it becomes possible to retrieve the image data beside the text. In the traditional way, we find the content of image by the tagged image with some indexed text. With the development of machine learning technique in the domain of artificial intelligence, the feature extraction techniques become easier for CBIR. The medical images are continuously increasing day by day where each image holds some specific and unique information about some specific disease. The objectives of using CBIR in medical diagnosis are to provide correct and effective information to the specialist for the quality and efficient diagnosis of the disease. Medical image content requires different types of CBIR technique for different medical image acquisition techniques such as MRI, CT, PET Scan, USG, MRS, etc. So, in this concern, each CBIR technique has its unique feature extraction algorithm for each acquisition technique.

Related Content

Aylin Gökhan, Kubilay Dogan Kilic, Türker Çavuşoğlu, Yiğit Uyanıkgil. © 2024. 12 pages.
Pratyush Panda, Subhalaxmi Das. © 2024. 21 pages.
Vikram Singh, Sangeeta Rani. © 2024. 17 pages.
Pancham Singh, Mrignainy Kansal, Shirshendu Lahiri, Harshit Vishnoi, Lakshay Mittal. © 2024. 19 pages.
Shreeharsha Dash, Subhalaxmi Das. © 2024. 16 pages.
V. Sathya, Shalini Parthiban, M. Megavarshini, V. Shenbagaraman, R. Ramya. © 2024. 13 pages.
Olalekan Joel Awujoola, Theophilus Enem Aniemeka, Oluwasegun Abiodun Abioye, Abidemi Elizabeth Awujoola, Fiyinfoluwa Ajakaiye, Olayinka Racheal Adelegan. © 2024. 34 pages.
Body Bottom