Abstract
Purpose: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. Materials and methods: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. Results: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor. Conclusion: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.
| Original language | English |
|---|---|
| Pages (from-to) | 125-133 |
| Number of pages | 9 |
| Journal | International journal of computer assisted radiology and surgery |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2018 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2017, The Author(s).
Keywords
- Interventional radiology
- Machine learning
- Magnetic resonance imaging
- Motion compensation
- Percutaneous needle insertion
- Respiratory motion
ASJC Scopus subject areas
- Surgery
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Health Informatics
- Computer Graphics and Computer-Aided Design
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