title: Needle detection in curvilinear ultrasound images based on the reflection pattern of circular ultrasound waves.
abstract: OBJECTIVE
  Ultrasound imaging provides a low-cost, real-time modality to guide needle insertion procedures, but localizing the needle using conventional ultrasound images is often challenging. Estimating the needle trajectory can increase the success rate of ultrasound-guided needle interventions and improve patient comfort. In this study, a novel method is introduced to localize the needle trajectory in curvilinear ultrasound images based on the needle reflection pattern of circular ultrasound waves.
  
  
  METHODS
  A circular ultrasound wave was synthesized by sequentially firing the elements of a curvilinear transducer and recording the radio-frequency signals received by each element. Two features, namely, the large amplitude and repetitive reflection pattern, were used to identify the needle echoes in the received signals. The trajectory of the needle was estimated by fitting the arrival times of needle echoes to an equation that describes needle reflection of circular waves. The method was employed to estimate the trajectories of needles inserted in agar phantom, beef muscle, and porcine tissue specimens.
  
  
  RESULTS
  The maximum error rates of estimating the needle trajectories were on the order of 1 mm and 3° for the radial and azimuth coordinates, respectively.
  
  
  CONCLUSIONS
  These results suggest that the proposed method can improve the robustness and accuracy of needle segmentation methods by adding signature-based detection of the needle trajectory in curvilinear ultrasound images. The method can be implemented on conventional ultrasound imaging systems.
authors.affiliation: Department of Computer Engineering, German Jordanian University, Amman 11180, Jordan.
authors.forename: Mohammad I
authors.initials: MI
authors.lastname: Daoud
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
authors.forename: Robert N
authors.initials: RN
authors.lastname: Rohling
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
authors.forename: Septimiu E
authors.initials: SE
authors.lastname: Salcudean
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
authors.forename: Purang
authors.initials: P
authors.lastname: Abolmaesumi
mesh_terms: D000465:Algorithms; D061765:Endoscopic Ultrasound-Guided Fine Needle Aspiration / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009339:Needles; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D018084:Ultrasonography, Interventional / Q000295:instrumentation / Q000379:methods*