3 research outputs found
Improving Surgical Situational Awareness with Signed Distance Field: A Pilot Study in Virtual Reality
The introduction of image-guided surgical navigation (IGSN) has greatly
benefited technically demanding surgical procedures by providing real-time
support and guidance to the surgeon during surgery. \hi{To develop effective
IGSN, a careful selection of the surgical information and the medium to present
this information to the surgeon is needed. However, this is not a trivial task
due to the broad array of available options.} To address this problem, we have
developed an open-source library that facilitates the development of multimodal
navigation systems in a wide range of surgical procedures relying on medical
imaging data. To provide guidance, our system calculates the minimum distance
between the surgical instrument and the anatomy and then presents this
information to the user through different mechanisms. The real-time performance
of our approach is achieved by calculating Signed Distance Fields at
initialization from segmented anatomical volumes. Using this framework, we
developed a multimodal surgical navigation system to help surgeons navigate
anatomical variability in a skull base surgery simulation environment. Three
different feedback modalities were explored: visual, auditory, and haptic. To
evaluate the proposed system, a pilot user study was conducted in which four
clinicians performed mastoidectomy procedures with and without guidance. Each
condition was assessed using objective performance and subjective workload
metrics. This pilot user study showed improvements in procedural safety without
additional time or workload. These results demonstrate our pipeline's
successful use case in the context of mastoidectomy.Comment: First two authors contributed equally. 6 page
Robot-Assisted Deep Venous Thrombosis Ultrasound Examination using Virtual Fixture
Deep Venous Thrombosis (DVT) is a common vascular disease with blood clots
inside deep veins, which may block blood flow or even cause a life-threatening
pulmonary embolism. A typical exam for DVT using ultrasound (US) imaging is by
pressing the target vein until its lumen is fully compressed. However, the
compression exam is highly operator-dependent. To alleviate intra- and
inter-variations, we present a robotic US system with a novel hybrid force
motion control scheme ensuring position and force tracking accuracy, and soft
landing of the probe onto the target surface. In addition, a path-based virtual
fixture is proposed to realize easy human-robot interaction for repeat
compression operation at the lesion location. To ensure the biometric
measurements obtained in different examinations are comparable, the 6D scanning
path is determined in a coarse-to-fine manner using both an external RGBD
camera and US images. The RGBD camera is first used to extract a rough scanning
path on the object. Then, the segmented vascular lumen from US images are used
to optimize the scanning path to ensure the visibility of the target object. To
generate a continuous scan path for developing virtual fixtures, an arc-length
based path fitting model considering both position and orientation is proposed.
Finally, the whole system is evaluated on a human-like arm phantom with an
uneven surface.Comment: Accepted Paper IEEE T-AS