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Super-resolution T2-weighted 4D MRI for image guided radiotherapy.

Joshua N Freedman | David J Collins | Oliver J Gurney-Champion | Jamie R McClelland | Simeon Nill | Uwe Oelfke | Martin O Leach | Andreas Wetscherek
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology | 2018

The superior soft-tissue contrast of 4D-T2w MRI motivates its use for delineation in radiotherapy treatment planning. We address current limitations of slice-selective implementations, including thick slices and artefacts originating from data incompleteness and variable breathing.

Pubmed ID: 29871813

Research resources used in this publication

None found

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Antibodies used in this publication

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Associated grants

  • Agency: Cancer Research UK, United Kingdom
    Id: C1060/A16464
  • Agency: Cancer Research UK, United Kingdom
    Id: C33589/A19727
  • Agency: Cancer Research UK, United Kingdom
    Id: C347/A18365
  • Agency: Cancer Research UK, United Kingdom
    Id: C309/A20926
  • Agency: Cancer Research UK, United Kingdom
    Id: C7224/A23275

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NiftyReg (tool)

RRID:SCR_006593

Software tools for global and local image registration. The algorithm used for global registration is based on a block matching approach enabling robust registration (outliers rejection). The local registration implementation uses a cubic B-Spline parametrisation (Free-Form Deformation). All registration algorithms are based on symmetric approaches where forward and backward transformations can be optimised concurrently. NiftyReg has been implemented for both CPU and GPU (through the use of CUDA).

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