Qiwen Yao,Chengyu Zhang,Qiang Lin et al.
Qiwen Yao et al.
Purpose: Flexible endoscopic robots hold broad application prospects in gastrointestinal tract surgery. However, the lack of intuitiveness and heterogeneity between the interface and flexible endoscopic robots results in ...
Real-time marker-less needle tracking for CT-guided interventions using multiple RGB cameras [0.03%]
Max Steiger,Tonia Mielke,Oleksii Bashkanov et al.
Max Steiger et al.
Purpose: In CT-guided interventions, instrument tracking reduces patient risk while improving the overall outcome. Though useful, marker-based tracking systems suffer from occlusion, are complex to set up, and fail when n...
BronchOpt: vision-based pose optimization with fine-tuned foundation models for accurate bronchoscopy navigation [0.03%]
Hongchao Shu,Roger D Soberanis-Mukul,Jiru Xu et al.
Hongchao Shu et al.
Purpose: Accurate intra-operative localization of the endoscope tip relative to the anatomy remains a major challenge in bronchoscopy due to respiratory motion, anatomical variability, and CT-to-body divergence, which cau...
Manuel Villa,Jaime Sancho,Gonzalo Rosa-Olmeda et al.
Manuel Villa et al.
Purpose: This study proposes the fusion of hyperspectral imaging (HSI) and magnetic resonance imaging (MRI) for tumor delineation in image-guided neurosurgery, comparing three clinically inspired registration strategies a...
Bernhard Michael Weber,Mathilde Connan,Alexander Kirst et al.
Bernhard Michael Weber et al.
Purpose: While laparoscopic procedures offer considerable advantages for the patient, they pose substantial challenges for the surgeon, whose hand-eye coordination is impaired. One reason for this is the surgeon's lost vi...
Minh Nguyen Nhat To,Diane Kim,Mohamed Harmanani et al.
Minh Nguyen Nhat To et al.
Purpose: Many medical AI models perform unevenly across patient groups because they learn shortcuts from biased data. These hidden biases make models less reliable and less fair in real-world use. This work aims to develo...
Deep learning-based renal artery segmentation and angle estimation for registration of endoscopic images and 3D models in robot-assisted partial nephrectomy [0.03%]
Keiji Tsukino,Satoshi Kobayashi,Shunsuke Takashima et al.
Keiji Tsukino et al.
Purpose: Image-guided robot-assisted partial nephrectomy (RAPN) that incorporates three-dimensional (3D) models has improved both oncological and functional outcomes. However, registration between the physical endoscopic ...
Suam Kim,Andrea Kronfeld,Sebastian R Reder et al.
Suam Kim et al.
Purpose: Digital Subtraction Angiography (DSA) is an X-ray-based imaging modality intimately related to minimally invasive procedures in interventional radiology, cardiology, vascular and neurologic surgery. Emulating tom...
Evaluating data heterogeneity's impact on convolutional neural network performance in medical imaging [0.03%]
数据异质性对医学影像卷积神经网络性能影响的评估
John Valen,Lucie Yang,Jacob Levman et al.
John Valen et al.
Purpose: Machine learning in medical imaging (MIML) is critical to computer-aided diagnostics. However, data heterogeneity-variation in medical data across sources and conditions-remains underexplored, despite its impact ...
Path planning for fracture reduction robots incorporating physiological tissue response and safety-oriented optimization [0.03%]
基于生理组织响应和安全优化的骨折复位机器人路径规划方法研究
Pengyun Liu,QianXin Wang,Bin Shi et al.
Pengyun Liu et al.
Purpose: Robot-assisted orthopedic reduction faces the dual challenge of achieving geometric precision while preserving physiological safety. This study presents a physiology-driven, multi-objective path-planning framewor...