Neumann M, Cuvillon L, Breton E, de Matheli M. Evaluation of an image-based tracking workflow with Kalman filtering for automatic image plane alignment in interventional MRI.
ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2013;
2013:2968-71. [PMID:
24110350 DOI:
10.1109/embc.2013.6610163]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Recently, a workflow for magnetic resonance (MR) image plane alignment based on tracking in real-time MR images was introduced. The workflow is based on a tracking device composed of 2 resonant micro-coils and a passive marker, and allows for tracking of the passive marker in clinical real-time images and automatic (re-)initialization using the microcoils. As the Kalman filter has proven its benefit as an estimator and predictor, it is well suited for use in tracking applications. In this paper, a Kalman filter is integrated in the previously developed workflow in order to predict position and orientation of the tracking device. Measurement noise covariances of the Kalman filter are dynamically changed in order to take into account that, according to the image plane orientation, only a subset of the 3D pose components is available. The improved tracking performance of the Kalman extended workflow could be quantified in simulation results. Also, a first experiment in the MRI scanner was performed but without quantitative results yet.
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