A Systematic Review on the Use of Registration-Based Change Tracking Methods in Longitudinal Radiological Images.
Registration is the process of spatially and/or temporally aligning different images. It is a critical tool that can facilitate the automatic tracking of pathological changes detected in radiological images and align images captured by different imaging systems and/or those acquired using different...
| Publicado en: | Journal of Imaging Informatics in Medicine Vol. 38; no. 4; pp. 2549 - 2563 |
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| Autores principales: | , , , , |
| Formato: | diagnostic images research systematic review tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=187278970&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187278970 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 29482925 NR3A jtl: Journal of Imaging Informatics in Medicine issn: 29482925 maglogo: N pubinfo: dt: Aug2025 vid: 38 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 187278970 187278970 187278970 10.1007/s10278-024-01333-1 187278970 ppf: 2549 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Systematic Review on the Use of Registration-Based Change Tracking Methods in Longitudinal Radiological Images. aug: au: Im, Jeeho E. Khalifa, Muhammed Gregory, Adriana V. Erickson, Bradley J. Kline, Timothy L. affil: https://ror.org/02qp3tb03 Department of Radiology, Mayo Clinic, 200 First St SW, 55905, Rochester, MN, USA sug: subj: Neoplasms Radiography Multiple Sclerosis Radiography Magnetic Resonance Imaging Methods Tomography, X-Ray Computed Methods Image Processing, Computer Assisted Methods Disease Progression Human Systematic Review United States PubMed Automation Oncologic Care Image Interpretation, Computer Assisted ab: Registration is the process of spatially and/or temporally aligning different images. It is a critical tool that can facilitate the automatic tracking of pathological changes detected in radiological images and align images captured by different imaging systems and/or those acquired using different acquisition parameters. The longitudinal analysis of clinical changes has a significant role in helping clinicians evaluate disease progression and determine the most suitable course of treatment for patients. This study provides a comprehensive review of the role registration-based approaches play in automated change tracking in radiological imaging and explores the three types of registration approaches which include rigid, affine, and nonrigid registration, as well as methods of detecting and quantifying changes in registered longitudinal images: the intensity-based approach and the deformation-based approach. After providing an overview and background, we highlight the clinical applications of these methods, specifically focusing on computed tomography (CT) and magnetic resonance imaging (MRI) in tumors and multiple sclerosis (MS), two of the most heavily studied areas in automated change tracking. We conclude with a discussion and recommendation for future directions. pubtype: Academic Journal doctype: diagnostic images research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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