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.
By Sho Mitarai, Hikaru Kayo, Hisashi Ozaki, Yuichiro Imai, Megumi Nakao
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.
By Fabi Nahian Madhurja, Rusab Sarmun, Muhammad E. H. Chowdhury, Adam Mushtak, Israa Al-Hashimi, Sohaib Bassam Zoghoul
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.
By Minheng Chen, Youyong Kong
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...
By Ahmed Aboelela, Johannes Barcsay, Jana Friedhof, Miguel Gon\c{c}alves, Alexander Hann, Katharina Breininger
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.
By Galib Ahmed, Istiak Ahmed, Aritra Islam Saswato, Asib Mostakim Fony, Kazi Shahriar Sanjid, Md. Tanzim Hossain, Md. Anwarul Islam, Md. Nishan Khan, Md. Misbah Khan, Labiba Faiza Karim, Jobaer Rahman, S M Hasibul Hoque, Rahnuma Shahrin Rista, Kamruzzaman Rumman, Md Arifur Rahman, Syed Md. Akram Hussain, Mohammad Ashrafuzzaman Khan, M. Monir Uddin
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.
By Yifei Wu, Yicheng Wu, Qiang Ma, Qi Chen, Renyang Gu, Xinyu Liu, Yongsheng Pan, Yong Xia