Coherent needle detection in ultrasound volumes using 3D conditional random fields

Farhad Ghazvinian Zanjani, Arash Pourtaherian, Xikai Tang, Svitlana Zinger, Nenad Mihajlovic, Gary C. Ng, Hendrikus H.M. Korsten, Peter H.N. de With

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
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3D ultrasound (US) transducers will improve the quality of image-guided medical interventions if an automated detection of the needle becomes possible. Image-based detection of the needle is challenging due to the presence of other echogenic structures in the acquired data, inconsistent visibility of needle parts and the low quality in US imaging. As the currently applied approaches for needle detection classify each voxel individually, they do not consider the global relations between the voxels. In this work, we introduce coherent needle labeling by using dense conditional random fields over a volume, along with 3D space-frequency features. The proposal includes long-distance dependencies in voxel pairs according to their similarities in the feature space and their spatial distance. This post-processing stage leads to better label assignment of volume voxels and a more compact and coherent segmented region. Our ex-vivo experiments based on measuring the F-1, F-2 and IoU scores show that the performance improves a significant 10-20 % compared with only using the linear SVM as a baseline for voxel classification.

Original languageEnglish
Title of host publicationMedical Imaging 2018
Subtitle of host publicationImage-Guided Procedures, Robotic Interventions, and Modeling
EditorsB. Fei, R.J. Webster
Place of PublicationBellingham
ISBN (Electronic)9781510616417
Publication statusPublished - 13 Mar 2018
EventSPIE Medical Imaging 2018 - Houston, United States
Duration: 10 Feb 201815 Feb 2018

Publication series

NameProceedings of SPIE


ConferenceSPIE Medical Imaging 2018
Country/TerritoryUnited States


  • 3D ultrasound
  • Conditional Random Fields
  • Needle detection


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