Motion estimation and correction for simultaneous PET/MR using SIRF and CIL

被引：8

作者：

Brown, Richard ^{[1
,2
]}

Kolbitsch, Christoph ^{[2
,3
]}

Delplancke, Claire ^{[4
]}

Papoutsellis, Evangelos ^{[5
,6
]}

Mayer, Johannes ^{[3
]}

Ovtchinnikov, Evgueni ^{[5
]}

Pasca, Edoardo ^{[5
]}

Neji, Radhouene ^{[2
,7
]}

Costa-luis, Casper da ^{[2
]}

Gillman, Ashley G. ^{[8
]}

Ehrhardt, Matthias J. ^{[4
,9
]}

McClelland, Jamie R. ^{[10
,11
]}

Eiben, Bjoern ^{[10
,11
]}

Thielemans, Kris ^{[1
,11
]}

机构：

[1] UCL, Inst Nucl Med, London, England

[2] Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England

[3] Phys Tech Bundesanstalt, Braunschweig, Germany

[4] Univ Bath, Dept Math Sci, Bath, Avon, England

[5] Rutherford Appleton Lab, STFC, Sci Comp Dept, UKRI, Harwell Campus, Didcot, Oxon, England

[6] Univ Manchester, Henry Royce Inst, Dept Mat, Manchester, Lancs, England

[7] Siemens Healthcare, MR Res Collaborat, Frimley, England

[8] CSIRO, Australian E Hlth Res Ctr, Townsville, Qld, Australia

[9] Univ Bath, Inst Math Innovat, Bath, Avon, England

[10] UCL, Ctr Med Image Comp, London, England

[11] UCL, Dept Med Phys & Biomed Engn, London, England

来源：

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2021年 / 379卷 / 2204期

基金：

英国工程与自然科学研究理事会;

关键词：

Motion; correction; estimation; PET; MR; SIRF; RESPIRATORY MOTION; IMAGE-RECONSTRUCTION; GENERALIZED RECONSTRUCTION; JOINT ESTIMATION; MRI; MODELS; COMPENSATION; INVERSION; FRAMEWORK; SOFTWARE;

D O I：

10.1098/rsta.2020.0208

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF's recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF's integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

引用

页数：16

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