To improve the surgeon’s visualization, the SIM lab is developing navigation algorithms with deformation compensation for tracking and displaying the instrument tip position and shape in a 3D patient-specific anatomical display.
Real-time Nonrigid Mosaicking of Laparoscopy Images
H. Zhou, J. Jayender
IEEE Transactions on Medical Imaging, 2021
To improve the surgeon’s dexterity, the SIM lab is developing robotic devices to provide remote access to the anatomy through a minimally invasive approach.
On Surgical Planning of Percutaneous Nephrolithotomy with Patient-Specific CTRs
F. Pedrosa , N. Feizi, R. Zhang, R. Delaunay, D. Sacco, J. Jayender, R.V. Patel
MICCAI, 2022
The third area of interest involving machine learning has led to the development of fast and robust deep learning based segmentation and registration algorithms for intraoperative use.
F3RNet: Full-Resolution Residual Registration Network for Deformable Image Registration
Z. Xu., J. Luo, J. Yan, X. Li, and J. Jayender
International Journal of Computer Assisted Radiology and Surgery, 2021