Literature DB >> 26952729

MR Imaging-Guided Partial Volume Correction of PET Data in PET/MR Imaging.

Kjell Erlandsson1, John Dickson2, Simon Arridge3, David Atkinson4, Sebastien Ourselin5, Brian F Hutton6.   

Abstract

Partial volume effects are caused by the limited spatial resolution of the PET system. There is increasing evidence that partial volume correction (PVC) is necessary to guarantee quantitative accuracy in PET; however, there is reluctance to apply PVC routinely in clinical practice, partly because of uncertainty regarding the method of choice. To perform accurate PVC, it is necessary to introduce information from high-resolution anatomic images, such as MR imaging. All the methods rely on accurate coregistration between the anatomic image and the PET image. PET/MR imaging offers clear advantages for PVC and can help alleviate the image registration issues.
Copyright © 2016 Elsevier Inc. All rights reserved.

Keywords:  PET/MR imaging; Partial volume correction; Partial volume effects; Quantification

Mesh:

Year:  2015        PMID: 26952729     DOI: 10.1016/j.cpet.2015.09.002

Source DB:  PubMed          Journal:  PET Clin        ISSN: 1556-8598


  10 in total

1.  Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.

Authors:  Hossein Arabi; Guodong Zeng; Guoyan Zheng; Habib Zaidi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-07-01       Impact factor: 9.236

2.  Noise suppressed partial volume correction for cardiac SPECT/CT.

Authors:  Chung Chan; Hui Liu; Yariv Grobshtein; Mitchel R Stacy; Albert J Sinusas; Chi Liu
Journal:  Med Phys       Date:  2016-09       Impact factor: 4.071

Review 3.  What scans we will read: imaging instrumentation trends in clinical oncology.

Authors:  Thomas Beyer; Luc Bidaut; John Dickson; Marc Kachelriess; Fabian Kiessling; Rainer Leitgeb; Jingfei Ma; Lalith Kumar Shiyam Sundar; Benjamin Theek; Osama Mawlawi
Journal:  Cancer Imaging       Date:  2020-06-09       Impact factor: 3.909

Review 4.  MRI-Driven PET Image Optimization for Neurological Applications.

Authors:  Yuankai Zhu; Xiaohua Zhu
Journal:  Front Neurosci       Date:  2019-07-31       Impact factor: 4.677

5.  Iterative framework for image registration and partial volume correction in brain positron emission tomography.

Authors:  Keisuke Matsubara; Masanobu Ibaraki; Miho Shidahara; Toshibumi Kinoshita
Journal:  Radiol Phys Technol       Date:  2020-10-19

6.  Brain partial volume correction with point spreading function reconstruction in high-resolution digital PET: comparison with an MR-based method in FDG imaging.

Authors:  Masanobu Ibaraki; Keisuke Matsubara; Yuki Shinohara; Miho Shidahara; Kaoru Sato; Hiroyuki Yamamoto; Toshibumi Kinoshita
Journal:  Ann Nucl Med       Date:  2022-05-26       Impact factor: 2.258

7.  DeepPVC: prediction of a partial volume-corrected map for brain positron emission tomography studies via a deep convolutional neural network.

Authors:  Keisuke Matsubara; Masanobu Ibaraki; Toshibumi Kinoshita
Journal:  EJNMMI Phys       Date:  2022-07-30

Review 8.  MR/PET Imaging of the Cardiovascular System.

Authors:  Philip M Robson; Damini Dey; David E Newby; Daniel Berman; Debiao Li; Zahi A Fayad; Marc R Dweck
Journal:  JACC Cardiovasc Imaging       Date:  2017-10

9.  Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit.

Authors:  Jagan A Pillai; Mykol Larvie; Jacqueline Chen; Anna Crawford; Jeffery L Cummings; Stephen E Jones
Journal:  Sci Rep       Date:  2020-11-26       Impact factor: 4.379

10.  Error propagation analysis of seven partial volume correction algorithms for [18F]THK-5351 brain PET imaging.

Authors:  Senri Oyama; Ayumu Hosoi; Masanobu Ibaraki; Colm J McGinnity; Keisuke Matsubara; Shoichi Watanuki; Hiroshi Watabe; Manabu Tashiro; Miho Shidahara
Journal:  EJNMMI Phys       Date:  2020-09-14
  10 in total

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