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dc.contributor.authorChen, Xin
dc.contributor.authorVarley, Martin R
dc.contributor.authorShark, Lik-Kwan
dc.contributor.authorShentall, Glyn S
dc.contributor.authorKirby, Mike C
dc.date.accessioned2009-05-22T14:17:57Z
dc.date.available2009-05-22T14:17:57Z
dc.date.issued2008-02-21
dc.identifier.citationA computationally efficient method for automatic registration of orthogonal x-ray images with volumetric CT data. 2008, 53 (4):967-83 Phys Med Biolen
dc.identifier.issn0031-9155
dc.identifier.pmid18263952
dc.identifier.doi10.1088/0031-9155/53/4/010
dc.identifier.urihttp://hdl.handle.net/10541/68836
dc.description.abstractThe paper presents a computationally efficient 3D-2D image registration algorithm for automatic pre-treatment validation in radiotherapy. The novel aspects of the algorithm include (a) a hybrid cost function based on partial digitally reconstructed radiographs (DRRs) generated along projected anatomical contours and a level set term for similarity measurement; and (b) a fast search method based on parabola fitting and sensitivity-based search order. Using CT and orthogonal x-ray images from a skull and a pelvis phantom, the proposed algorithm is compared with the conventional ray-casting full DRR based registration method. Not only is the algorithm shown to be computationally more efficient with registration time being reduced by a factor of 8, but also the algorithm is shown to offer 50% higher capture range allowing the initial patient displacement up to 15 mm (measured by mean target registration error). For the simulated data, high registration accuracy with average errors of 0.53 mm +/- 0.12 mm for translation and 0.61 +/- 0.29 degrees for rotation within the capture range has been achieved. For the tested phantom data, the algorithm has also shown to be robust without being affected by artificial markers in the image.
dc.language.isoenen
dc.subject.meshAlgorithms
dc.subject.meshAutomatic Data Processing
dc.subject.meshCone-Beam Computed Tomography
dc.subject.meshHumans
dc.subject.meshImage Processing, Computer-Assisted
dc.subject.meshPelvis
dc.subject.meshPhantoms, Imaging
dc.subject.meshSkull
dc.titleA computationally efficient method for automatic registration of orthogonal x-ray images with volumetric CT data.en
dc.typeArticleen
dc.contributor.departmentADSIP Research Centre, University of Central Lancashire, Preston, UK. xchen2@uclan.ac.uken
dc.identifier.journalPhysics in Medicine and Biologyen
html.description.abstractThe paper presents a computationally efficient 3D-2D image registration algorithm for automatic pre-treatment validation in radiotherapy. The novel aspects of the algorithm include (a) a hybrid cost function based on partial digitally reconstructed radiographs (DRRs) generated along projected anatomical contours and a level set term for similarity measurement; and (b) a fast search method based on parabola fitting and sensitivity-based search order. Using CT and orthogonal x-ray images from a skull and a pelvis phantom, the proposed algorithm is compared with the conventional ray-casting full DRR based registration method. Not only is the algorithm shown to be computationally more efficient with registration time being reduced by a factor of 8, but also the algorithm is shown to offer 50% higher capture range allowing the initial patient displacement up to 15 mm (measured by mean target registration error). For the simulated data, high registration accuracy with average errors of 0.53 mm +/- 0.12 mm for translation and 0.61 +/- 0.29 degrees for rotation within the capture range has been achieved. For the tested phantom data, the algorithm has also shown to be robust without being affected by artificial markers in the image.


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