Tracking and visualization of the sensing area for a tethered laparoscopic gamma probe.
Image-guided surgery
Minimally invasive surgery
Pose estimation
Prostate cancer
Tethered laparoscopic gamma probe
Tracking
Journal
International journal of computer assisted radiology and surgery
ISSN: 1861-6429
Titre abrégé: Int J Comput Assist Radiol Surg
Pays: Germany
ID NLM: 101499225
Informations de publication
Date de publication:
Aug 2020
Aug 2020
Historique:
received:
19
11
2019
accepted:
27
05
2020
pubmed:
20
6
2020
medline:
15
12
2020
entrez:
20
6
2020
Statut:
ppublish
Résumé
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. 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. 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 [Formula: see text] and [Formula: see text], 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 [Formula: see text] and [Formula: see text]-[Formula: see text]-[Formula: see text] . 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.
Identifiants
pubmed: 32556919
doi: 10.1007/s11548-020-02205-z
pii: 10.1007/s11548-020-02205-z
pmc: PMC7351835
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1389-1397Subventions
Organisme : Department of Health
ID : NIHR200035
Pays : United Kingdom
Organisme : National Institute for Health Research
ID : NIHR200035
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