Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/15621
Title: Image Registration for 3D Medical Images
Authors: Nair, Rekha R
Babu, Tina
Keywords: Average Correlation Coefficient
Average Sum Of Squared Differences
Image Registration
Intensity Variance
Mutual Information
Issue Date: 2024
Publisher: Advances in Computers
Academic Press Inc.
Abstract: In order to maximize the similarity between the source images, image registration establishes the spatial connection over multiple sets of medical images. Three-dimensional images can be created using tomographic procedures including positron emission tomography, computed tomography, single-photon emission computed tomography, and magnetic resonance imaging (MRI). In general, patterns of geometry and picture gray values are used to register multimodal medical images. The most important step in 3D healthcare image synthesis is the image registration procedure. The goal of this chapter is to give a concise overview of 3D medical image registration categorization algorithms, images employed in fusion, assessment measures, and various transformations, with an emphasis on the most current research advancements. The survey's goals are to clarify the fundamental ideas behind some of the terminology used in the literature, examine a few algorithms, provide a general framework for classifying and contrasting algorithms, and direct readers to the literature for more in-depth explanations. Thus, regardless of specific application areas, the chapter offers researchers working on image registration a comprehensive source of reference information. © 2024 Elsevier Inc.
URI: http://dx.doi.org/10.1016/bs.adcom.2024.03.002
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/15621
ISSN: 0065-2458
Appears in Collections:Book/ Book Chapters

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.