arXiv:2608. 07116v1 Announce Type: cross Abstract: Camera localization in bronchoscopy remains a challenging problem due to stringent accuracy requirements, real-time constraints, and limited training data.
By Lumin Chen, Qingyao Tian, Jinpeng Li, Haoyu Jiang, Huai Liao, Xinyan Huang, Hongbin Liu, Dong Yi
arXiv:2609.37386v1 Announce Type: new
Abstract: Pre-operative planning for bronchoscopy is critical for the diagnosis of lung lesions. Current accessibility assessment relies on subjective manual ins...
By Linkai Peng, Cuiling Sun, Bin Wang, Jamie Rowell, Catherine Gao, Oyku Ikizgul, Eminenur Sentasci, Andrea Bejar, Halil Ertugrul Aktas, Gorkem Durak, Momen Wahidi, Christopher Kapp, Ulas Bagci
GRIPNet is a new CT‑based pulmonary nodule detector that incorporates a Gaussian radial intensity prior, reflecting the regular pattern of intensity peaks at nodule centers and Gaussian decay outward. By replacing generic square convolutions with pinwheel, dual‑frequency, dilated masked attention, and an adaptive loss, the network aligns each module with measurable intensity properties. The method achieves state‑of‑the‑art mAP@0.5 scores of 95.3%, 91.6%, and 97.9% on KanserSet, LUNA16, and Lung‑PET‑CT‑Dx, respectively, while maintaining real‑time speed and improving high‑IoU localization.
By Haojie Yang, Ran Su
arXiv:2607. 11949v1 Announce Type: cross Abstract: We present a clinically deployed end-to-end auto-contouring system for cervical cancer radiotherapy planning, anchored by the Boundary-Aware Transformer with Region-Aware Mamba (BAT-RM), a hybrid architecture that integrates Sobel-gated boundary attention, a linear-time, multi-directional Mamba module for long-range context, and a boundary-skeleton-guided fusion gate.
By Istiak Ahmed, Kazi Shahriar Sanjid, Galib Ahmed, Md. Tanzim Hossain, Md. Anwarul Islam, Shahrukh Khan, Md. Ashrif Rahman Arian, Md. Nishan Khan, Md. Misbah Khan, S M Hasibul Hoque, Rahnuma Shahrin Rista, Md. Jobairul Islam, Sheikh Anisul Haque, Md Arifur Rahman, Syed Md. Akram Hussain, Syeda Nashra, Sayeed Shafayet Chowdhury, Md. Mostafa Kamal Sarker, M. Monir Uddin
RAUL is a reference‑assisted reconstruction framework that recovers ureteroscope trajectories from endoscopic video alone, using a high‑quality reference exploration video for each phantom. It achieves a mean translation error of 0.5 mm and increases frame‑wise localization coverage from 50.5 % to 86.1 % compared to standard Structure‑from‑Motion. The reconstructed trajectories reveal significant differences in navigation metrics between high‑ and low‑experience trainees, enabling objective skill assessment without external tracking equipment.
By Fangjie Li, Mai Bui, Charan Mohan, Michael Miga, Matthieu Chabanas, Nicholas Kavoussi, Jie Ying Wu
arXiv:2608. 03430v1 Announce Type: cross Abstract: Four-dimensional cone beam CT (4D CBCT) is important for image-guided radiation therapy of thoracic cancers, but its use is limited by long scan times, causing high patient dose and motion/sparse-sampling artifacts.
By Ivo Herzig, Pascal Paysan, Daniel Barco, Marc Andr\'e Stadelmann, Frank-Peter Schilling, Igor Peterlik, Michal Walczak, Lijin Aryananda, Woo Sang Ahn, Rudolf Marcel F\"uchslin, Lukas Lichtensteiger