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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Uhercik, M. Kybic, J. Cachard, C. Liebgott, H. |
| Copyright Year | 2009 |
| Description | Author affiliation: Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic (Uhercik, M.; Kybic, J.) || CREATIS-LRMN, Universite de Lyon, INSA-Lyon, Universite Lyon 1, CNRS UMR 5220, Inserm U630, Villeurbanne, France (Cachard, C.; Liebgott, H.) |
| Abstract | We propose a robust method for localization of elongated surgical tools in 3D ultrasound data based on shape analysis. The tubular structures in input data are enhanced by a line filter in the pre-processing phase. A new model of a surgical tool appearance in 3D ultrasound image is proposed which exploits its tubular shape. The tool axis is estimated with robust model fitting using a randomized RANSAC procedure. The tool model requires the voxels close to the axis to have a high intensity, high tubularness, and the local principal directions to be consistent with the tool axis. The visual contrast of the tool can be enhanced four-fold using line filtering. We demonstrate that classification rate is improved by 25–40% when adding the tubularness attribute. The comparison to other state-of-the-art localization methods shows that the proposed method is the most robust for data with high level of noise at the expense of additional time for pre-processing (less than 10 seconds for volume of size 53×71×260 voxels). |
| Starting Page | 594 |
| Ending Page | 597 |
| File Size | 330010 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424443895 |
| ISSN | 19485727 |
| DOI | 10.1109/ULTSYM.2009.5441538 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-20 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Filtering Ultrasonic imaging Shape Noise robustness Needles Minimally invasive surgery Object detection Cybernetics Image segmentation Curve fitting |
| Content Type | Text |
| Resource Type | Article |
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