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Computer-Aided Diagnosis System of Alzheimer's Disease Based on Multimodal Fusion: Tissue Quantification Based on the Hybrid Fuzzy-Genetic-Possibilistic Model and Discriminative Classification Based on the SVDD Model.

Author(s): Lazli L, Boukadoum M, Ait Mohamed O

Brain Sci. 2019 Oct 22;9(10): Authors: Lazli L, Boukadoum M, Ait Mohamed O

Article GUID: 31652635

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

Author(s): Daoud MI, Alshalalfah AL, Ait Mohamed O, Alazrai R

Med Image Anal. 2018 12;50:145-166 Authors: Daoud MI, Alshalalfah AL, Ait Mohamed O, Alazrai R

Article GUID: 30336383


Title:A hybrid camera- and ultrasound-based approach for needle localization and tracking using a 3D motorized curvilinear ultrasound probe.
Authors:Daoud MIAlshalalfah ALAit Mohamed OAlazrai R
Link:https://www.ncbi.nlm.nih.gov/pubmed/30336383?dopt=Abstract
Category:Med Image Anal
PMID:30336383
Dept Affiliation: ENCS
1 Department of Computer Engineering, German Jordanian University, Amman, Jordan. Electronic address: mohammad.aldaoud@gju.edu.jo.
2 Department of Computer Engineering, German Jordanian University, Amman, Jordan.
3 Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada.

Description:

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

Med Image Anal. 2018 12;50:145-166

Authors: Daoud MI, Alshalalfah AL, Ait Mohamed O, Alazrai R

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.

PMID: 30336383 [PubMed - in process]