Literature DB >> 30336383

A hybrid camera- and ultrasound-based approach for needle localization and tracking using a 3D motorized curvilinear ultrasound probe.

Mohammad I Daoud1, Abdel-Latif Alshalalfah2, Otmane Ait Mohamed3, Rami Alazrai2.   

Abstract

Three-dimensional (3D) motorized curvilinear ultrasound probes provide an effective, low-cost tool to guide needle interventions, but localizing and tracking the needle in 3D ultrasound volumes is often challenging. In this study, a new method is introduced to localize and track the needle using 3D motorized curvilinear ultrasound probes. In particular, a low-cost camera mounted on the probe is employed to estimate the needle axis. The camera-estimated axis is used to identify a volume of interest (VOI) in the ultrasound volume that enables high needle visibility. This VOI is analyzed using local phase analysis and the random sample consensus algorithm to refine the camera-estimated needle axis. The needle tip is determined by searching the localized needle axis using a probabilistic approach. Dynamic needle tracking in a sequence of 3D ultrasound volumes is enabled by iteratively applying a Kalman filter to estimate the VOI that includes the needle in the successive ultrasound volume and limiting the localization analysis to this VOI. A series of ex vivo animal experiments are conducted to evaluate the accuracy of needle localization and tracking. The results show that the proposed method can localize the needle in individual ultrasound volumes with maximum error rates of 0.7 mm for the needle axis, 1.7° for the needle angle, and 1.2 mm for the needle tip. Moreover, the proposed method can track the needle in a sequence of ultrasound volumes with maximum error rates of 1.0 mm for the needle axis, 2.0° for the needle angle, and 1.7 mm for the needle tip. These results suggest the feasibility of applying the proposed method to localize and track the needle using 3D motorized curvilinear ultrasound probes.
Copyright © 2018 Elsevier B.V. All rights reserved.

Keywords:  3D ultrasound imaging; Camera-based needle localization; Kalman filter; Needle localization and tracking; RANSAC; Ultrasound-guided needle interventions

Mesh:

Year:  2018        PMID: 30336383     DOI: 10.1016/j.media.2018.09.006

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  2 in total

1.  Multi-Needle Detection in 3D Ultrasound Images Using Unsupervised Order-Graph Regularized Sparse Dictionary Learning.

Authors:  Yupei Zhang; Xiuxiu He; Zhen Tian; Jiwoong Jason Jeong; Yang Lei; Tonghe Wang; Qiulan Zeng; Ashesh B Jani; Walter J Curran; Pretesh Patel; Tian Liu; Xiaofeng Yang
Journal:  IEEE Trans Med Imaging       Date:  2020-01-22       Impact factor: 10.048

2.  Multi-needle Localization with Attention U-Net in US-guided HDR Prostate Brachytherapy.

Authors:  Yupei Zhang; Yang Lei; Richard L J Qiu; Tonghe Wang; Hesheng Wang; Ashesh B Jani; Walter J Curran; Pretesh Patel; Tian Liu; Xiaofeng Yang
Journal:  Med Phys       Date:  2020-04-03       Impact factor: 4.071

  2 in total

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