Presentation + Paper
16 March 2020 Automatic needle localization in intraoperative 3D transvaginal ultrasound images for high-dose-rate interstitial gynecologic brachytherapy
Author Affiliations +
Abstract
High-dose-rate interstitial gynecologic brachytherapy requires multiple needles to be inserted into the tumor and surrounding area, avoiding nearby healthy organs-at-risk (OARs), including the bladder and rectum. We propose the use of a 360° three-dimensional (3D) transvaginal ultrasound (TVUS) guidance system for visualization of needles and report on the implementation of two automatic needle segmentation algorithms to aid the localization of needles intraoperatively. Two-dimensional (2D) needle segmentation, allowing for immediate adjustments to needle trajectories to mitigate needle deflection and avoid OARs, was implemented in near real-time using a method based on a convolutional neural network with a U-Net architecture trained on a dataset of 2D ultrasound images from multiple applications with needle-like structures. In 18 unseen TVUS images, the median position difference [95% confidence interval] was 0.27 [0.20, 0.68] mm and mean angular difference was 0.50 [0.27, 1.16]° between manually and algorithmically segmented needles. Automatic needle segmentation was performed in 3D TVUS images using an algorithm leveraging the randomized 3D Hough transform. All needles were accurately localized in a proof-of-concept image with a median position difference of 0.79 [0.62, 0.93] mm and median angular difference of 0.46 [0.31, 0.62]°, when compared to manual segmentations. Further investigation into the robustness of the algorithm to complex cases containing large shadowing, air, or reverberation artefacts is ongoing. Intraoperative automatic needle segmentation in interstitial gynecologic brachytherapy has the potential to improve implant quality and provides the potential for 3D ultrasound to be used for treatment planning, eliminating the requirement for post-insertion CT scans.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jessica R. Rodgers, Derek J. Gillies, W. Thomas Hrinivich, Igor Gyackov, and Aaron Fenster "Automatic needle localization in intraoperative 3D transvaginal ultrasound images for high-dose-rate interstitial gynecologic brachytherapy", Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113150K (16 March 2020); https://doi.org/10.1117/12.2549664
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

3D image processing

Image processing algorithms and systems

Ultrasonography

3D acquisition

Visualization

Radiotherapy

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