ROOTFlow: 3D Tooth Root Synthesis from Intraoral Scans and Panoramic Radiographs via Latent Flow Matching

Three-dimensional tooth surface morphology and spatial arrangement are important for dental diagnosis and treatment planning. Intraoral scans (IOS) capture detailed crown surfaces but cannot reveal tooth roots, whose three-dimensional morphology and spatial arrangement typically require cone-beam computed tomography (CBCT) to assess, at the cost of additional radiation exposure. Panoramic X-ray (PX) images provide root-related morphological and spatial cues at a lower radiation dose, but their inherent depth ambiguity and geometric distortion limit accurate three-dimensional root reconstruction. We propose ROOTFlow (Root-Oriented Oral Tomography via Latent Flow Matching), a framework that combines IOS-derived crown geometry with radiographic context to generate quadrant-level CBCT volumes and corresponding tooth segmentations, focusing on root surface morphology and spatial arrangement. The framework comprises four components: (i) quadrant-level data construction, in which unsigned distance fields (UDFs) encode IOS meshes as volumetric geometric priors; (ii) latent representation learning with two 3D variational autoencoders that compress CBCT and UDF inputs; (iii) cross-modal contrastive alignment that maps CBCT and PX features into a shared representation space; and (iv) conditional 3D latent flow matching, in which a velocity network conditioned on UDF latent features and PX features guides flow integration to generate a CBCT latent representation. The generated latent representation is jointly decoded into a quadrant-level CBCT volume and corresponding tooth segmentation. PX features provide complementary morphological and contextual cues rather than metrically reliable three-dimensional measurements. We construct a quadrant-level dataset comprising matched CBCT–IOS–PX trios derived from 5,682 patients. Evaluations using general and root-specific metrics demonstrate that ROOTFlow outperforms all evaluated baselines, with improved geometric fidelity of synthesized tooth root surfaces and more accurate tooth positioning.