Towards Seamless Integration of Magnetic Tracking into Fluoroscopy-guided Interventions

The 2D projective nature of X-ray radiography presents significant limitations in fluoroscopy-guided interventions, particularly the loss of depth perception and prolonged radiation exposure. Integrating magnetic trackers into these workflows is promising; however, it remains challenging and under-explored in current research and practice. To address this, we employed a radiolucent magnetic field generator (FG) prototype as a foundational step towards seamless magnetic tracking (MT) integration. A two-layer FG mounting frame was designed for compatibility with various C-arm X-ray systems, ensuring smooth installation and optimal tracking accuracy. To overcome technical challenges, including accurate C-arm pose estimation, robust fluoro-CT registration, and 3D navigation, we proposed the incorporation of external aluminum fiducials without disrupting conventional workflows. Experimental evaluation showed no clinically significant impact of the aluminum fiducials and the C-arm on MT accuracy. Our fluoro-CT registration demonstrated high accuracy (mean projection distance approxiamtely 0.7 mm, robustness (wide capture range), and generalizability across local and public datasets. In a phantom targeting experiment, needle insertion error was between 2 mm and 3 mm, with real-time guidance using enhanced 2D and 3D navigation. Overall, our results demonstrated the efficacy and clinical applicability of the MT-assisted approach. To the best of our knowledge, this is the first study to integrate a radiolucent FG into a fluoroscopy-guided workflow.

Stereo Correspondence and Reconstruction of Endoscopic Data Challenge

The stereo correspondence and reconstruction of endoscopic data sub-challenge was organized during the Endovis challenge at MICCAI 2019 in Shenzhen, China. The task was to perform dense depth estimation using 7 training datasets and 2 test sets of structured light data captured using porcine cadavers. These were provided by a team at Intuitive Surgical. 10 teams participated in the challenge day. This paper contains 3 additional methods which were submitted after the challenge finished as well as a supplemental section from these teams on issues they found with the dataset.