An Augmented Reality Application for Visualizing Anatomical Data



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Augmented Reality can be useful in medical science because the visualization of a patient's internal structure is important for planning an intervention. Traditional display technologies present images collected from CT, MRI or ultrasound on 2D screens. However, aligning those images to a patient's body helps physicians decide the target of the intervention. In this thesis, an iPad application is proposed, which overlays 3D models of a patient's organs acquired using MRI scan in real-time video. The process is divided into two parts: 1) 3D registration and 2) tracking. The registration consists of acquiring the 3D structure of patient's torso using a depth sensor and overlaying pre-operative 3D models in real-time video. This is accomplished by a 3D point-to-point registration using the Iterative Closest Point algorithm. The tracking keeps the 3D models aligned on the patient's body by detecting the camera's pose. This is accomplished by using a technique called Simultaneous Localization and Mapping, which maps the environment and estimates the camera pose continuously. Registration accuracy is measured based on a study of eight different users of the application. The possibility of porting the application to a head-mounted display or glasses is also explored.



Medical visualization, Augmented reality, Depth sensor, Image registration, Medical imaging, Iterative Closest Point, Simultaneous Localization and Mapping, Camera Pose