Nikhil V. Navkar

TL;DR: This approach provides both real-time visualization and force-feedback based guidance for maneuvering an interventional tool safely inside the dynamic environment of a heart's left ventricle and demonstrates improvement in control and manipulation.

TL;DR: A technique for simple and efficient visualization of the region of intervention for neurosurgical procedures through the generation of access maps on the surface of the patient's skin, which assists a neurosurgeon in selecting the most appropriate path of access by avoiding vital structures and minimizing potential trauma to healthy tissue is proposed.

TL;DR: A variational framework to track the motion of moving objects in surgery videos and a robust energy functional based on Bhattacharyya coefficient to match the target region in the first frame of the input sequence with the subsequent frames using a similarity metric is developed.

TL;DR: In this article, the authors present systems, modules and methods of using the same for in-situ real-time imaging guidance of a robot during a surgical procedure, which are configured to operate in at least one computer having a memory, a processor and a network connection to enable instructions to generally control the imaging modality, track the robot, track a tissue of interest in an area of procedure, process data acquired from imaging modalities, and visualize the area and robot.

TL;DR: A proposed GPU-accelerated method enables interactive quantitative estimation of the risk for a particular path and exploits acceleration spatial data structures and efficient implementation of algorithms on GPUs to achieve interactive rates even for high-resolution meshes.