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Live Image-based Neurosurgical Guidance and Roadmap Generation Using Unsupervised Embedding by Sarwin, Gary; Carretta, Alessandro; Staartjes, Victor; Zoli, Matteo; Mazzatenta, Diego; Regli, Luca; Serra, Carlo; Konukoglu, Ender is a scholarly article available to read on EtoBox.

What is Live Image-based Neurosurgical Guidance and Roadmap Generation Using Unsupervised Embedding about?

Advanced minimally invasive neurosurgery navigation relies mainly on Magnetic Resonance Imaging (MRI) guidance. MRI guidance, however, only provides pre-operative information in the majority of the cases. Once the surgery begins, the value of this guidance diminishes to some extent because of the anatomical changes due to surgery. Guidance with live image feedback coming directly from the surgical device, e.g., endoscope, can complement MRI-based navigation or be an alternative if MRI guidance is not feasible. With this motivation, we present a method for live image-only guidance leveraging a large data set of annotated neurosurgical videos.First, we report the performance of a deep learning-based object detection method, YOLO, on detecting anatomical structures in neurosurgical images. Second, we present a method for generating neurosurgical roadmaps using unsupervised embedding without assuming exact anatomical matches between patients, presence of an extensive anatomical atlas, or the need for simultaneous localization and mapping. A generated roadmap encodes the common anatomical paths taken in surgeries in the training set. At inference, the roadmap can be used to map a surgeo

Author

Sarwin, Gary; Carretta, Alessandro; Staartjes, Victor; Zoli, Matteo; Mazzatenta, Diego; Regli, Luca; Serra, Carlo; Konukoglu, Ender

Published

2023

Language

EN