aceComparative evaluation of VoxelMorpand conventional deformable image registration algorithms for thoracic 4D-CT in radiotherapy
Background Deformable image registration (DIR) is essential for thoracic four-dimensional computed tomography (4D-CT)-based radiotherapy applications. Recently, deep learning-based DIR methods such as VoxelMorph have been proposed; however, their performance relative to clinically used DIR algorithms remains unclear. Purpose This study aimed to evaluate the DIR accuracy of VoxelMorph for thoracic 4D-CT and to compare it with conventional clinical and research-oriented DIR methods. Materials and methods Thoracic…
VoxelMorph achieved comparable deformable registration accuracy to clinical algorithms on thoracic 4D-CT, reaching 0.98 median lung Dice and 36.83 HU median MAE with shorter processing times in the evaluated implementation.
Findings are limited to a small test set of 10 cases from a single retrospective cohort of 64 patients and to the specific implementation conditions, requiring further validation under standardized conditions before routine clinical use.
Evidence
- Peer-reviewedJournal of Applied Clinical Medical Physics2026-10-01
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Truvace Impact Record TRV-2026-1237, v1: “Comparative evaluation of VoxelMorpand conventional deformable image registration algorithms for thoracic 4D-CT in radiotherapy.” Truvace, 2026-10-01. /record/TRV-2026-1237 (accessed at citation time). sha256 8976fe971dc267d3…
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