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Báo cáo hóa học: "Research Article Evaluation of a Validation Method for MR Imaging-Based Motion Tracking Using Image Simulation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Evaluation of a Validation Method for MR Imaging-Based Motion Tracking Using Image Simulation | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 942131 11 pages doi 10.1155 2010 942131 Research Article Evaluation of a Validation Method for MR Imaging-Based Motion Tracking Using Image Simulation Kevin M. Moerman 1 Christian M. Kerskens 2 Caitriona Lally 3 Vittoria Flamini 3 and Ciaran K. Simms1 1 Trinity Centre for Bioengineering School of Engineering Parsons Building Trinity College Dublin 2 Ireland 2Trinity College Institute of Neuroscience Trinity College Dublin Dublin Ireland 3Mechanical and Manufacturing Engineering Dublin City University Dublin Ireland Correspondence should be addressed to Kevin M. Moerman moermank@tcd.ie Received 1 May 2009 Accepted 20 July 2009 Academic Editor Joao Manuel R. S. Tavares Copyright 2010 Kevin M. Moerman et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Magnetic Resonance MR imaging-based motion and deformation tracking techniques combined with finite element FE analysis are a powerful method for soft tissue constitutive model parameter identification. However deriving deformation data from MR images is complex and generally requires validation. In this paper a validation method is presented based on a silicone gel phantom containing contrasting spherical markers. Tracking ofthese markers provides a direct measure of deformation. Validation of in vivo medical imaging techniques is often challenging due to the lack of appropriate reference data and the validation method may lack an appropriate reference. This paper evaluates a validation method using simulated MR image data. This provided an appropriate reference and allowed different error sources to be studied independently and allowed evaluation of the method for various signal-to-noise ratios SNRs . The geometric bias error was between 0-5.560 X 10 .