Abstract
In many medical image-guided navigation systems (IGNS), image-to-patient registration plays an important part for applying reliable anatomical information mapping and spatial guidance. In this study, we propose a totally non-contact image-to-patient registration technique using kinect sensor and an ICP-based (Iterative Closest Point-based) registration algorithm which is named WAP-ICP. A Kinect sensor is used to detect facial feature points form a patient and calculate 3D coordinates of these points. The WAP-ICP algorithm can help us to register these 3D points to the surface reconstructed from the patient’s preoperative CT images without pre-alignment. Moreover, WAP-ICP altgorithm uses not only a random-perturbation technique to deal with the local minimum problem of ICP, but also a weighting strategy to reject noisy feature points. Experimental results reveal that the proposed WAP-ICP algorithm has great improvement in robustness than the ICP algorithm.
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Hsieh, CH., Huang, CH., Lee, JD. (2013). A Non-contact Image-to-Patient Registration Method Using Kinect Sensor and WAP-ICP. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2012. Studies in Computational Intelligence, vol 443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32172-6_8
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DOI: https://doi.org/10.1007/978-3-642-32172-6_8
Publisher Name: Springer, Berlin, Heidelberg
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