Neural Deformable Cone Beam CT

Simple item page
dc.contributor.authorBirklein, Lukasen_US
dc.contributor.authorSchömer, Elmaren_US
dc.contributor.authorBrylka, Roberten_US
dc.contributor.authorSchwanecke, Ulrichen_US
dc.contributor.authorSchulze, Ralfen_US
dc.contributor.editorHansen, Christianen_US
dc.contributor.editorProcter, Jamesen_US
dc.contributor.editorRenata G. Raidouen_US
dc.contributor.editorJönsson, Danielen_US
dc.contributor.editorHöllt, Thomasen_US
dc.date.accessioned2023-09-19T11:31:47Z
dc.date.available2023-09-19T11:31:47Z
dc.date.issued2023
dc.description.abstractIn oral and maxillofacial cone beam computed tomography (CBCT), patient motion is frequently observed and, if not accounted for, can severely affect the usability of the acquired images. We propose a highly flexible, data driven motion correction and reconstruction method which combines neural inverse rendering in a CBCT setting with a neural deformation field. We jointly optimize a lightweight coordinate based representation of the 3D volume together with a deformation network. This allows our method to generate high quality results while accurately representing occurring patient movements, such as head movements, separate jaw movements or swallowing. We evaluate our method in synthetic and clinical scenarios and are able to produce artefact-free reconstructions even in the presence of severe motion. While our approach is primarily developed for maxillofacial applications, we do not restrict the deformation field to certain kinds of motion. We demonstrate its flexibility by applying it to other scenarios, such as 4D lung scans or industrial tomography settings, achieving state-of-the art results within minutes with only minimal adjustments.en_US
dc.description.sectionheadersRadiology and Histopathology
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20231211
dc.identifier.isbn978-3-03868-216-5
dc.identifier.issn2070-5786
dc.identifier.pages41-50
dc.identifier.pages10 pages
dc.identifier.urihttps://doi.org/10.2312/vcbm.20231211
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20231211
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Reconstruction; Volumetric models; Motion processing; Neural networks
dc.subjectComputing methodologies
dc.subjectReconstruction
dc.subjectVolumetric models
dc.subjectMotion processing
dc.subjectNeural networks
dc.titleNeural Deformable Cone Beam CTen_US
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
041-050.pdf
Size:
32.24 MB
Format:
Adobe Portable Document Format
Download
Collections
VCBM 2023: Eurographics Workshop on Visual Computing for Biology and Medicine