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Decoupling of respiratory motion with wavelet and principal component analysis

Fani Deligianni, Adrian Chung, Guang-Zhong Yang

Conference or Workshop Paper
Medical Image Understanding and Analysis (MIUA04)

The establishment of patient specific models for minimal access surgical simulation requires the acquisition and co-registration of 2D endoscope/laparoscope video with 3D tomographic data with matched physiological status. The advent of in vivo catheter tip tracking devices offers the potential for improving the robustness and accuracy of current registration techniques in the presence of tissue deformation. For bronchoscope simulation, reliable extraction of respiratory motion allows retrospective gating of the acquired tracking data so that video bronchoscope views can be grouped according to different respiratory phases. In practice, the motion data recorded is coupled with patient and respiratory motion and the decoupling of the two is not trivial. This paper presents a novel motion decoupling technique for simplifying 2D/3D registration under the influence of normal respiratory motion. Wavelet analysis has been used to identify and remove episodes due to coughing and extreme breathing patterns. The technique has been validated with data acquired from 8 subjects, demonstrating the practical value of the proposed method.

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