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Tracking and visualization of the sensing area for a tethered laparoscopic gamma probe
File | Description | Size | Format | |
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Huang2020_Article_TrackingAndVisualizationOfTheS.pdf | Published version | 1.33 MB | Adobe PDF | View/Open |
Title: | Tracking and visualization of the sensing area for a tethered laparoscopic gamma probe |
Authors: | Huang, B Tsai, Y-Y Cartucho, J Vyas, K Tuch, D Giannarou, S Elson, DS |
Item Type: | Journal Article |
Abstract: | Purpose In surgical oncology, complete cancer resection and lymph node identification are challenging due to the lack of reliable intraoperative visualization. Recently, endoscopic radio-guided cancer resection has been introduced where a novel tethered laparoscopic gamma detector can be used to determine the location of tracer activity, which can complement preoperative nuclear imaging data and endoscopic imaging. However, these probes do not clearly indicate where on the tissue surface the activity originates, making localization of pathological sites difficult and increasing the mental workload of the surgeons. Therefore, a robust real-time gamma probe tracking system integrated with augmented reality is proposed. Methods A dual-pattern marker has been attached to the gamma probe, which combines chessboard vertices and circular dots for higher detection accuracy. Both patterns are detected simultaneously based on blob detection and the pixel intensity-based vertices detector and used to estimate the pose of the probe. Temporal information is incorporated into the framework to reduce tracking failure. Furthermore, we utilized the 3D point cloud generated from structure from motion to find the intersection between the probe axis and the tissue surface. When presented as an augmented image, this can provide visual feedback to the surgeons. Results The method has been validated with ground truth probe pose data generated using the OptiTrack system. When detecting the orientation of the pose using circular dots and chessboard dots alone, the mean error obtained is 0.05∘ and 0.06∘, respectively. As for the translation, the mean error for each pattern is 1.78 mm and 1.81 mm. The detection limits for pitch, roll and yaw are 360∘,360∘ and 8∘–82∘∪188∘–352∘ . Conclusion The performance evaluation results show that this dual-pattern marker can provide high detection rates, as well as more accurate pose estimation and a larger workspace than the previously proposed hybrid markers. The augmented reality will be used to provide visual feedback to the surgeons on the location of the affected lymph nodes or tumor. |
Issue Date: | 1-Aug-2020 |
Date of Acceptance: | 27-May-2020 |
URI: | http://hdl.handle.net/10044/1/80746 |
DOI: | 10.1007/s11548-020-02205-z |
ISSN: | 1861-6410 |
Publisher: | Springer Verlag |
Start Page: | 1389 |
End Page: | 1397 |
Journal / Book Title: | International Journal of Computer Assisted Radiology and Surgery |
Volume: | 15 |
Copyright Statement: | © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Sponsor/Funder: | Imperial College Healthcare NHS Trust- BRC Funding Imperial College Healthcare NHS Trust- BRC Funding Cancer Research UK Imperial College Healthcare NHS Trust- BRC Funding National Institute for Health Research |
Funder's Grant Number: | RDB04 79560 RD207 25147 RDB04 NIHR200035 |
Keywords: | Science & Technology Technology Life Sciences & Biomedicine Engineering, Biomedical Radiology, Nuclear Medicine & Medical Imaging Surgery Engineering Image-guided surgery Prostate cancer Tethered laparoscopic gamma probe Minimally invasive surgery Pose estimation Tracking Image-guided surgery Minimally invasive surgery Pose estimation Prostate cancer Tethered laparoscopic gamma probe Tracking Science & Technology Technology Life Sciences & Biomedicine Engineering, Biomedical Radiology, Nuclear Medicine & Medical Imaging Surgery Engineering Image-guided surgery Prostate cancer Tethered laparoscopic gamma probe Minimally invasive surgery Pose estimation Tracking Nuclear Medicine & Medical Imaging 1103 Clinical Sciences |
Publication Status: | Published |
Open Access location: | https://link.springer.com/article/10.1007/s11548-020-02205-z |
Online Publication Date: | 2020-06-16 |
Appears in Collections: | Department of Surgery and Cancer Institute of Global Health Innovation |