Evidence map›Paper›PMID 41972990›Full record

ArticleJournal of X-ray science and technology2026

Branchless distance-driven and hybrid projectors in iterative cone beam CT.

Ville-Veikko Wettenhovi, Ari Hietanen, Nargiza Djurabekova, Kati Niinimäki, Marko Vauhkonen, Ville Kolehmainen

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Article in Journal of X-ray science and technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Ville-Veikko WettenhoviDepartment of Technical Physics, University of Eastern Finland, Finland.ORCID 0000-0002-4427-9109
Ari HietanenPlanmeca Group, Helsinki, Finland.ORCID 0000-0002-1944-423X
Nargiza DjurabekovaPlanmeca Group, Helsinki, Finland.ORCID 0000-0001-7521-5653
Kati NiinimäkiPlanmeca Group, Helsinki, Finland.
Marko VauhkonenDepartment of Technical Physics, University of Eastern Finland, Finland.ORCID 0000-0001-6454-8524
Ville KolehmainenDepartment of Technical Physics, University of Eastern Finland, Finland.ORCID 0000-0002-5621-795X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PurposeIterative model-based image reconstruction algorithms in cone beam computed tomography (CBCT) require repetitive forward and backward projection operations. We compare the quality of the branchless distance-driven (BDD) projector in iterative CBCT reconstruction with ray- and voxel-based methods in both regular and low-dose examinations, and introduce a hybrid approach that aims at faster computation by using the BDD as the backprojector only. We also demonstrate the potential of the BDD in FDK reconstructions.ApproachTwo measured and one simulated datasets are used. Contrast-to-noise ratio (CNR) and modulation transfer function values are computed for one measured dataset. The structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) are computed with the simulated data.ResultsBased on our results, BDD has reduced noise and better CNR compared to the other methods, with the quality dependent on the scanner geometry. The CNR is improved by 21% with the BDD and 4% with the hybrid method. BDD improves SSIM values by approximately 3.3% in the lowest dose case and 1% in the highest dose case, while for PSNR the values are 5% - 10% better. For the hybrid method, the SSIM improvements range from 0.8% - 2.2%, and the PSNR from 3.7% - 6.6 %. The hybrid method with the BDD as a backprojector can be computationally twice faster with similar image quality.ConclusionsThe hybrid projector is a good choice as a compromise between image quality and computation time. Furthermore, BDD and the hybrid projector are better choices in low-dose CBCT reconstructions.

Indexed as

Cone-Beam Computed TomographyImage Processing, Computer-AssistedAlgorithmsComputer SimulationHumansPhantoms, ImagingSignal-To-Noise Ratiocone beam computed tomographydistance-drivenimage reconstructionmodel-based iterativeprojector

Identifiers

PMID41972990
PMCPMC13333037

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.