MO-DE-210-05: Improved Accuracy of Liver Feature Motion Estimation in B-Mode Ultrasound for Image-Guided Radiation Therapy

Authors


Abstract

Purpose:

In similarity-measure based motion estimation incremental tracking (or template update) is challenging due to quantization, bias and accumulation of tracking errors. A method is presented which aims to improve the accuracy of incrementally tracked liver feature motion in long ultrasound sequences.

Methods:

Liver ultrasound data from five healthy volunteers under free breathing were used (15 to 17 Hz imaging rate, 2.9 to 5.5 minutes in length). A normalised cross-correlation template matching algorithm was implemented to estimate tissue motion. Blood vessel motion was manually annotated for comparison with three tracking code implementations: (i) naive incremental tracking (IT), (ii) IT plus a similarity threshold (ST) template-update method and (iii) ST coupled with a prediction-based state observer, known as the alpha-beta filter (ABST).

Results:

The ABST method produced substantial improvements in vessel tracking accuracy for two-dimensional vessel motion ranging from 7.9 mm to 40.4 mm (with mean respiratory period: 4.0 ± 1.1 s). The mean and 95% tracking errors were 1.6 mm and 1.4 mm, respectively (compared to 6.2 mm and 9.1 mm, respectively for naive incremental tracking).

Conclusions:

High confidence in the output motion estimation data is required for ultrasound-based motion estimation for radiation therapy beam tracking and gating. The method presented has potential for monitoring liver vessel translational motion in high frame rate B-mode data with the required accuracy.

This work is support by Cancer Research UK Programme Grant C33589/A19727.

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