Paper
8 December 2015 Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound
Arash Pourtaherian, Svitlana Zinger, Nenad Mihajlovic, Peter H. N. de With, Jinfeng Huang, Gary C. Ng, Hendrikus H. M. Korsten
Author Affiliations +
Proceedings Volume 9875, Eighth International Conference on Machine Vision (ICMV 2015); 987513 (2015) https://doi.org/10.1117/12.2228604
Event: Eighth International Conference on Machine Vision, 2015, Barcelona, Spain
Abstract
Ultrasound imaging is employed for needle guidance in various minimally invasive procedures such as biopsy guidance, regional anesthesia and brachytherapy. Unfortunately, a needle guidance using 2D ultrasound is very challenging, due to a poor needle visibility and a limited field of view. Nowadays, 3D ultrasound systems are available and more widely used. Consequently, with an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. In this paper, we present a multi-resolution Gabor transformation for an automated and reliable extraction of the needle-like structures in a 3D ultrasound volume. We study and identify the best combination of the Gabor wavelet frequencies. High precision in detecting the needle voxels leads to a robust and accurate localization of the needle for the intervention support. Evaluation in several ex-vivo cases shows that the multi-resolution analysis significantly improves the precision of the needle voxel detection from 0.23 to 0.32 at a high recall rate of 0.75 (gain 40%), where a better robustness and confidence were confirmed in the practical experiments.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arash Pourtaherian, Svitlana Zinger, Nenad Mihajlovic, Peter H. N. de With, Jinfeng Huang, Gary C. Ng, and Hendrikus H. M. Korsten "Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound", Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 987513 (8 December 2015); https://doi.org/10.1117/12.2228604
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Cited by 3 scholarly publications.
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KEYWORDS
Ultrasonography

Wavelets

Feature extraction

3D image processing

3D modeling

Biopsy

Data modeling

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