Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

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Kalman Filter-based EM-optical Sensor Fusion for Needle Deflection Estimation

Institution:
1School of Mechanical Engineering, Tianjin University, Tianjin, China. baichuan@tju.edu.cn.
2 School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
3Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
4Robin Medical Inc., Baltimore, MD, USA.
5Department of Neuroradiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publisher:
Springer
Publication Date:
Apr-2018
Journal:
Int J Comput Assist Radiol Surg
Volume Number:
13
Issue Number:
4
Pages:
573-83
Citation:
Int J Comput Assist Radiol Surg. 2018 Apr;13(4):573-83.
PubMed ID:
29417355
PMCID:
PMC590344
Keywords:
Kalman filter (KF), Needle deflection estimation, Sensor fusion, Surgical navigation
Appears in Collections:
NCIGT, SPL
Sponsors:
P41 EB015898/National Center for Research Resources/United States
P41 RR019703/National Institute of Biomedical Imaging and Bioengineering/United States
81201150/National Natural Science Foundation of China/United States
2012M520741/China Postdoctoral Science Foundation/United States
Generated Citation:
Jiang B., Gao W., Kacher D., Nevo E., Fetics B., Lee T.C., Jayender J. Kalman Filter-based EM-optical Sensor Fusion for Needle Deflection Estimation. Int J Comput Assist Radiol Surg. 2018 Apr;13(4):573-83. PMID: 29417355. PMCID: PMC590344.
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PURPOSE: In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects. METHODS: In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach. RESULTS: Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively. CONCLUSION: This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.