Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation maps
We introduce a computationally efficient approach to the generation of Digital Reconstructed Radiographs (DRRs) needed to perform three dimensional to two dimensional medical image registration and apply this algorithm to virtual surgery. The DRR generation process is the bottleneck of any three dim...
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AIMS Press
2012-06-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.527 |
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| author | Luca Bertelli Frédéric Gibou |
| author_facet | Luca Bertelli Frédéric Gibou |
| author_sort | Luca Bertelli |
| collection | DOAJ |
| description | We introduce a computationally efficient approach to the generation of Digital Reconstructed Radiographs (DRRs) needed to perform three dimensional to two dimensional medical image registration and apply this algorithm to virtual surgery. The DRR generation process is the bottleneck of any three dimensional to two dimensional registration system, since its computational complexity scales with the number of voxels in the Computed Tomography Data, which can be of the order of tens to hundreds of millions. Our approach originates from the segmentation of the volumetric data into multiple regions, which allows a compact representation viaOctree Data Structures. This, in turn, yields efficient storage and access of the attenuation indexes of the volumetric cells, required in the projection procedure that generates the DRR. A functional based on Mutual Information is then maximized to obtain the alignment of the DRR with the two dimensional X-ray fluoroscopy scansacquired during the operation. Promising experimental results on real data are presented. |
| format | Article |
| id | doaj-art-d1ed902a5e824a1282f0dde5a8c5f078 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2012-06-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-d1ed902a5e824a1282f0dde5a8c5f0782025-01-24T02:07:00ZengAIMS PressMathematical Biosciences and Engineering1551-00182012-06-019352753710.3934/mbe.2012.9.527Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation mapsLuca Bertelli0Frédéric Gibou1ECE Department, UCSB, Santa Barbara, CA 93106ECE Department, UCSB, Santa Barbara, CA 93106We introduce a computationally efficient approach to the generation of Digital Reconstructed Radiographs (DRRs) needed to perform three dimensional to two dimensional medical image registration and apply this algorithm to virtual surgery. The DRR generation process is the bottleneck of any three dimensional to two dimensional registration system, since its computational complexity scales with the number of voxels in the Computed Tomography Data, which can be of the order of tens to hundreds of millions. Our approach originates from the segmentation of the volumetric data into multiple regions, which allows a compact representation viaOctree Data Structures. This, in turn, yields efficient storage and access of the attenuation indexes of the volumetric cells, required in the projection procedure that generates the DRR. A functional based on Mutual Information is then maximized to obtain the alignment of the DRR with the two dimensional X-ray fluoroscopy scansacquired during the operation. Promising experimental results on real data are presented.https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.527digital reconstructed radiographyoctree mesh generation. |
| spellingShingle | Luca Bertelli Frédéric Gibou Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation maps Mathematical Biosciences and Engineering digital reconstructed radiography octree mesh generation. |
| title | Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation maps |
| title_full | Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation maps |
| title_fullStr | Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation maps |
| title_full_unstemmed | Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation maps |
| title_short | Fast two dimensional to three dimensional registration of fluoroscopy and CT-scans using Octrees on segmentation maps |
| title_sort | fast two dimensional to three dimensional registration of fluoroscopy and ct scans using octrees on segmentation maps |
| topic | digital reconstructed radiography octree mesh generation. |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.527 |
| work_keys_str_mv | AT lucabertelli fasttwodimensionaltothreedimensionalregistrationoffluoroscopyandctscansusingoctreesonsegmentationmaps AT fredericgibou fasttwodimensionaltothreedimensionalregistrationoffluoroscopyandctscansusingoctreesonsegmentationmaps |