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.
Farhad Ghazvinian Zanjani, Arash Pourtaherian, Xikai Tang, Svitlana Zinger, Nenad Mihajlovic, Gary C. Ng, Hendrikus H. M. Korsten, and Peter H. N. de With, "Coherent needle detection in ultrasound volumes using 3D conditional random fields," Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105760W (Presented at SPIE Medical Imaging: February 14, 2018; Published: 13 March 2018); https://doi.org/10.1117/12.2293079.
Conference Presentations are recordings of oral presentations given at SPIE conferences and published as part of the conference proceedings. They include the speaker's narration along with a video recording of the presentation slides and animations. Many conference presentations also include full-text papers. Search and browse our growing collection of more than 14,000 conference presentations, including many plenary and keynote presentations.
Study of self-shadowing effect as a simple means to realize nanostructured thin films and layers with special attentions to birefringent obliquely deposited thin films and photo-luminescent porous silicon