Relevance-Based Visualization to Improve Surgeon Perception.
Lecture Notes in Computer Science(2014)
摘要
In computer-aided interventions, the visual feedback of the doctor is vital. Enhancing the relevant object will help for the perception of this feedback. In this paper, we present a learning-based labeling of the surgical scene using a depth camera (comprised of RGB and depth range sensors). The depth sensor is used for background extraction and Random Forests are used for segmenting color images. The end result is a labeled scene consisting of surgeon hands, surgical instruments and background labels. We evaluated the method by conducting 10 simulated surgeries with 5 clinicians and demonstrated that the approach provides surgeons a dissected surgical scene, enhanced visualization, and upgraded depth perception.
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关键词
visualization, medical augmented reality, machine learning, multimodal image fusion, operating room
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