Validation of a non-rigid registration method for motion compensation in 4D ultrasound of the liver
Future therapy using focused ultrasound (FUS) to treat tumors in abdominal organs, such as the liver, must incorporate motion tracking of these organs due to breathing and drift caused by gravity and intestines (peristalsis). Motion tracking of the target (e.g. tumor) is needed to ensure accurately located sonications. We have performed a quantitative validation of a methodology for motion tracking of the liver with 4D (3D+time) ultrasound. The offline analysis was done using a recently published non-rigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D sequence in a group-wise optimization fashion, thus avoiding a bias towards a specifically chosen reference time point. Both spatial and temporal smoothness of the transformations are enforced by using a 4D free-form B-spline deformation model. For our evaluation, three healthy volunteers were scanned over several breath cycles from three different positions and angles on the abdomen (totally nine 4D scans). A skilled physician performed the scanning and manually annotated well-defined anatomic landmarks for assessment of the automatic algorithm. Four engineers each annotated these points in all time frames, the mean of which was taken as a gold standard. The error of the automatic motion estimation method was compared with inter-observer variability. The registration method estimated liver motion better than the observers and had an error (75% percentile over all datasets) of 1 mm. We conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data.
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|2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013|
Vijayan, S, Klein, S, Hofstad, E.F, Lindseth, F, Ystgaard, B, & Langø, T. (2013). Validation of a non-rigid registration method for motion compensation in 4D ultrasound of the liver. Presented at the 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013. doi:10.1109/ISBI.2013.6556594