arXiv:2607. 10551v1 Announce Type: cross Abstract: Accurate geometric calibration is essential for fluoroscopy-guided spinal imaging, digitally reconstructed radiograph (DRR) generation, and 2D--3D vertebral registration.
arXiv:2608. 07564v1 Announce Type: cross Abstract: In digital dentistry and oral surgery, the registration of jawbone CT and intraoral scanner (IOS) data is essential for integrating internal bone structure with high-resolution dental surface geometry.
arXiv:2601. 15235v4 Announce Type: replace-cross Abstract: Cervical spine fractures require rapid and accurate diagnosis, yet automatic CT interpretation remains challenging as subtle injuries must be assessed across large 3D volumes.
arXiv:2607. 23343v1 Announce Type: cross Abstract: Intraoperative 2D/3D registration aligns preoperative CT volumes with intraoperative X-ray or fluoroscopic images and is essential for image-guided interventions.
arXiv:2609.24560v1 Announce Type: new Abstract: Confocal Laser Endomicroscopy (CLE) provides real-time, cellular-resolution optical biopsy but has a narrow field of view, which image mosaicing can ex...
The paper introduces DAMM‑Net++, a 2.5D neural network for thoracic organ‑at‑risk and target volume segmentation that tackles inter‑slice surface incoherence, small low‑contrast target failure, and lack of per‑case reliability signals. Its core is an anatomy‑change‑aware bidirectional selective state‑space memory that propagates context across axial slices, complemented by a boundary‑aware decoder and an uncertainty head for calibrated per‑voxel confidence. Evaluations on 2,146 patients, an external cohort, and a reader study show high Dice scores (0.955), low HD95 (3.78 mm), significant time savings (75‑80 %) for clinicians, and improved junior‑reader performance, with the system fully integrated into a clinical workflow.
The paper introduces LiftXR, a geometry‑guided framework that first reconstructs a 3D anatomical layout from bi‑planar X‑ray images and then uses this layout to guide CT volume reconstruction. An anatomical parser refines the layout by analyzing the reconstructed CT, enabling region‑specific intensity calibration. Experiments on two public datasets show LiftXR surpasses recent X‑ray‑to‑CT methods and improves downstream segmentation performance.
arXiv:2608.22131v1 Announce Type: cross Abstract: Craniosynostosis severity analysis increasingly relies on statistical shape models (SSMs) to quantify cranial morphology, but most existing workflows...
The study introduces the RSM framework, which includes the ARNAI artifact removal network, to enhance automated measurement of spinopelvic parameters on postoperative lumbar spine radiographs containing implants. Adding ARNAI to the Transformer-based FCBFormer model raised the mean Dice similarity coefficient from 0.814 to 0.870 and significantly reduced the mean L4–L5 segmental Cobb angle error from about 15.8° to 4.7°, a 70% improvement. The framework also improved intraclass correlation coefficients for key parameters, surpassing 0.70 for pelvic tilt, lumbar lordosis, and sacral slope.
The paper examines how residual misalignments from registration procedures introduce structured label noise in supervised synthetic CT (sCT) generation. It shows that voxel‑wise metrics are heavily influenced by the consistency between training and evaluation registrations, and that training with anatomically consistent registrations reduces variability and improves robustness. Introducing a perceptual loss based on a pretrained Segment Anything encoder yields sharper, more anatomically coherent sCT and highlights the need for anatomy‑oriented evaluation.
The paper introduces a geometric adaptation framework for cross‑speaker acoustic‑to‑articulatory inversion that leverages anatomical landmarks on vertebrae and dental structures. By applying an affine transformation followed by a thin‑plate spline deformation, the method maps predicted vocal‑tract contours from a fixed model to unseen speakers without retraining. Experiments on a single‑speaker rt‑MRI database and eight additional speakers show that the combined affine‑plus‑TPS approach with 12 and 14 landmarks yields the lowest mean point‑to‑closest‑point error of 3.19 mm.
arXiv:2606. 19867v1 Announce Type: cross Abstract: Computed Tomography (CT) is essential for diagnosing pediatric craniofacial abnormalities, yet poses radiation risks to developing anatomies.
arXiv:2608.28705v1 Announce Type: cross Abstract: Dose accumulation is increasingly important in adaptive radiation therapy and reirradiation, but its clinical validity depends on the performance of...