Synergistic tomographic image reconstruction: part 1

被引:1
|
作者
Tsoumpas, Charalampos [1 ,2 ,3 ]
Jorgensen, Jakob Sauer [4 ,5 ]
Kolbitsch, Christoph [6 ,7 ,8 ]
Thielemans, Kris [9 ]
机构
[1] Univ Leeds, Biomed Imaging Sci Dept, Leeds, W Yorkshire, England
[2] Icahn Sch Med Mt Sinai, Biomed Engn & Imaging Inst, New York, NY 10029 USA
[3] Invicro, London, England
[4] Tech Univ Denmark, Dept Appl Math & Comp Sci, Lyngby, Denmark
[5] Univ Manchester, Dept Math, Manchester, Lancs, England
[6] Phys Tech Bundesanstalt, Braunschweig, Germany
[7] Phys Tech Bundesanstalt, Berlin, Germany
[8] Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England
[9] UCL, Inst Nucl Med, London, England
基金
英国工程与自然科学研究理事会;
关键词
positron emission tomography; computed tomography; magnetic resonance imaging; electrical impedance tomography; tomography; imaging;
D O I
10.1098/rsta.2020.0189
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
This special issue focuses on synergistic tomographic image reconstruction in a range of contributions in multiple disciplines and various application areas. The topic of image reconstruction covers substantial inverse problems (Mathematics) which are tackled with various methods including statistical approaches (e.g. Bayesian methods, Monte Carlo) and computational approaches (e.g. machine learning, computational modelling, simulations). The issue is separated in two volumes. This volume focuses mainly on algorithms and methods. Some of the articles will demonstrate their utility on real-world challenges, either medical applications (e.g. cardiovascular diseases, proton therapy planning) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issue is to bring together different scientific communities which do not usually interact as they do not share the same platforms (such as journals and conferences). This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.
引用
收藏
页数:5
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