Generalized Automatic Probe Alignment based on 3D Ultrasound
Jonas Osburg, Daniel L. Wulff, Floris Ernst
- Year
- 2022
- Citations
- 2
- Access
- Open access
Abstract
Abstract Acquiring reproducible ultrasound images of high quality is challenging in ultrasound imaging. While physicians can rely on their experience, robot-assisted systems must be able to automatically align the ultrasound probe with the correct orientation. This paper describes a method to align the central axis of the probe to the surface normal at the point of contact. This is done by analyzing the area of ultrasound volumes directly below the transducer of the probe. A convolutional neural network is trained to estimate the inclination of the probe orientation towards the direction of the surface normal. Experiments on two different phantoms indicate that the mean absolute angle error between the estimated rotation and the ground truth surface normal are 5.0 ± 2.8∘. The method is able to keep the probe-surface contact continuous and the results indicate that the method is invariant to anatomical structures.
Keywords
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