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Vision-Based Neurosurgical Guidance: Unsupervised Localization and Camera-Pose Prediction
Localizing oneself during endoscopic procedures can be problematic due to the lack of distinguishable textures and landmarks, as well as difficulties due to the endoscopic device such as a limited field of view and challenging lighting conditions.
Live image-based neurosurgical guidance and roadmap generation using unsupervised embedding
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.
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