Literature DB >> 22435355

Medical image registration: a review.

Francisco P M Oliveira1, João Manuel R S Tavares.   

Abstract

This paper presents a review of automated image registration methodologies that have been used in the medical field. The aim of this paper is to be an introduction to the field, provide knowledge on the work that has been developed and to be a suitable reference for those who are looking for registration methods for a specific application. The registration methodologies under review are classified into intensity or feature based. The main steps of these methodologies, the common geometric transformations, the similarity measures and accuracy assessment techniques are introduced and described.

Mesh:

Year:  2012        PMID: 22435355     DOI: 10.1080/10255842.2012.670855

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  86 in total

Review 1.  The Applications of Genetic Algorithms in Medicine.

Authors:  Ali Ghaheri; Saeed Shoar; Mohammad Naderan; Sayed Shahabuddin Hoseini
Journal:  Oman Med J       Date:  2015-11

2.  Canny edge-based deformable image registration.

Authors:  Vasant Kearney; Yihui Huang; Weihua Mao; Baohong Yuan; Liping Tang
Journal:  Phys Med Biol       Date:  2017-01-12       Impact factor: 3.609

Review 3.  Image fusion during vascular and nonvascular image-guided procedures.

Authors:  Nadine Abi-Jaoudeh; Hicham Kobeiter; Sheng Xu; Bradford J Wood
Journal:  Tech Vasc Interv Radiol       Date:  2013-09

4.  BIRNet: Brain image registration using dual-supervised fully convolutional networks.

Authors:  Jingfan Fan; Xiaohuan Cao; Pew-Thian Yap; Dinggang Shen
Journal:  Med Image Anal       Date:  2019-03-22       Impact factor: 8.545

5.  Deformable Registration for Longitudinal Breast MRI Screening.

Authors:  Hatef Mehrabian; Lara Richmond; Yingli Lu; Anne L Martel
Journal:  J Digit Imaging       Date:  2018-10       Impact factor: 4.056

6.  Quicksilver: Fast predictive image registration - A deep learning approach.

Authors:  Xiao Yang; Roland Kwitt; Martin Styner; Marc Niethammer
Journal:  Neuroimage       Date:  2017-07-11       Impact factor: 6.556

7.  Assessment of registration accuracy during computer-aided oncologic limb-salvage surgery.

Authors:  Kurt E Stoll; Joan D Miles; Jedediah K White; Stephanie E W Punt; Ernest U Conrad; Randal P Ching
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-01-13       Impact factor: 2.924

8.  Automated registration of magnetic resonance imaging and optoacoustic tomography data for experimental studies.

Authors:  Wuwei Ren; Hlynur Skulason; Felix Schlegel; Markus Rudin; Jan Klohs; Ruiqing Ni
Journal:  Neurophotonics       Date:  2019-04-03       Impact factor: 3.593

9.  Discovering New Lipidomic Features Using Cell Type Specific Fluorophore Expression to Provide Spatial and Biological Specificity in a Multimodal Workflow with MALDI Imaging Mass Spectrometry.

Authors:  Marissa A Jones; Sung Hoon Cho; Nathan Heath Patterson; Raf Van de Plas; Jeffrey M Spraggins; Mark R Boothby; Richard M Caprioli
Journal:  Anal Chem       Date:  2020-05-06       Impact factor: 6.986

10.  Image Segmentation, Registration and Characterization in R with SimpleITK.

Authors:  Richard Beare; Bradley Lowekamp; Ziv Yaniv
Journal:  J Stat Softw       Date:  2018-09-04       Impact factor: 6.440

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