A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion
Abstract OrthoFusion, an intuitive super-resolution algorithm, is presented in this study to enhance the spatial resolution of clinical CT volumes. The efficacy of OrthoFusion is evaluated, relative to high-resolution CT volumes (ground truth), by assessing image volume and derived bone morphologica...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-85516-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841544706425618432 |
|---|---|
| author | Rebecca E. Abbott Alain Nishimwe Hadi Wiputra Ryan E. Breighner Arin M. Ellingson |
| author_facet | Rebecca E. Abbott Alain Nishimwe Hadi Wiputra Ryan E. Breighner Arin M. Ellingson |
| author_sort | Rebecca E. Abbott |
| collection | DOAJ |
| description | Abstract OrthoFusion, an intuitive super-resolution algorithm, is presented in this study to enhance the spatial resolution of clinical CT volumes. The efficacy of OrthoFusion is evaluated, relative to high-resolution CT volumes (ground truth), by assessing image volume and derived bone morphological similarity, as well as its performance in specific applications in 2D-3D registration tasks. Results demonstrate that OrthoFusion significantly reduced segmentation time, while improving structural similarity of bone images and relative accuracy of derived bone model geometries. Moreover, it proved beneficial in the context of biplane videoradiography, enhancing the similarity of digitally reconstructed radiographs to radiographic images and improving the accuracy of relative bony kinematics. OrthoFusion’s simplicity, ease of implementation, and generalizability make it a valuable tool for researchers and clinicians seeking high spatial resolution from existing clinical CT data. This study opens new avenues for retrospectively utilizing clinical images for research and advanced clinical purposes, while reducing the need for additional scans, mitigating associated costs and radiation exposure. |
| format | Article |
| id | doaj-art-e57a0af7e1d4469381b46a4f8873ebc8 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e57a0af7e1d4469381b46a4f8873ebc82025-01-12T12:20:43ZengNature PortfolioScientific Reports2045-23222025-01-0115111010.1038/s41598-025-85516-yA super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusionRebecca E. Abbott0Alain Nishimwe1Hadi Wiputra2Ryan E. Breighner3Arin M. Ellingson4Divisions of Physical Therapy and Rehabilitation Science, Department of Family Medicine and Community Health, University of MinnesotaDepartment of Biomedical Engineering, University of MinnesotaDepartment of Biomedical Engineering, University of MinnesotaDepartment of Radiology and Imaging, Hospital for Special SurgeryDivisions of Physical Therapy and Rehabilitation Science, Department of Family Medicine and Community Health, University of MinnesotaAbstract OrthoFusion, an intuitive super-resolution algorithm, is presented in this study to enhance the spatial resolution of clinical CT volumes. The efficacy of OrthoFusion is evaluated, relative to high-resolution CT volumes (ground truth), by assessing image volume and derived bone morphological similarity, as well as its performance in specific applications in 2D-3D registration tasks. Results demonstrate that OrthoFusion significantly reduced segmentation time, while improving structural similarity of bone images and relative accuracy of derived bone model geometries. Moreover, it proved beneficial in the context of biplane videoradiography, enhancing the similarity of digitally reconstructed radiographs to radiographic images and improving the accuracy of relative bony kinematics. OrthoFusion’s simplicity, ease of implementation, and generalizability make it a valuable tool for researchers and clinicians seeking high spatial resolution from existing clinical CT data. This study opens new avenues for retrospectively utilizing clinical images for research and advanced clinical purposes, while reducing the need for additional scans, mitigating associated costs and radiation exposure.https://doi.org/10.1038/s41598-025-85516-ySuper ResolutionBone modelsComputed tomographyImage FusionSpatial resolution enhancement |
| spellingShingle | Rebecca E. Abbott Alain Nishimwe Hadi Wiputra Ryan E. Breighner Arin M. Ellingson A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion Scientific Reports Super Resolution Bone models Computed tomography Image Fusion Spatial resolution enhancement |
| title | A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion |
| title_full | A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion |
| title_fullStr | A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion |
| title_full_unstemmed | A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion |
| title_short | A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion |
| title_sort | super resolution algorithm to fuse orthogonal ct volumes using orthofusion |
| topic | Super Resolution Bone models Computed tomography Image Fusion Spatial resolution enhancement |
| url | https://doi.org/10.1038/s41598-025-85516-y |
| work_keys_str_mv | AT rebeccaeabbott asuperresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT alainnishimwe asuperresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT hadiwiputra asuperresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT ryanebreighner asuperresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT arinmellingson asuperresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT rebeccaeabbott superresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT alainnishimwe superresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT hadiwiputra superresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT ryanebreighner superresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion AT arinmellingson superresolutionalgorithmtofuseorthogonalctvolumesusingorthofusion |