ArticleFrontiers in oncology2021
The Feasibility of Haar Feature-Based Endoscopic Ultrasound Probe Tracking for Implanting Hydrogel Spacer in Radiation Therapy for Pancreatic Cancer.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- XIOSIS: An X-Ray-Based Intra-Operative Image-Guided Platform for Oncology Smart Material Delivery.IEEE transactions on medical imaging · 2024Article
- Ultrasound Imaging with Flexible Array Transducer for Pancreatic Cancer Radiation Therapy.Cancers · 2023Article
- deepPERFECT: Novel Deep Learning CT Synthesis Method for Expeditious Pancreatic Cancer Radiotherapy.Cancers · 2023Article
- DAART: a deep learning platform for deeply accelerated adaptive radiation therapy for lung cancer.Frontiers in oncology · 2023Article
- Systematic study of the iodinated rectal hydrogel spacer material discrepancy on accuracy of proton dosimetry.Journal of applied clinical medical physics · 2022Article
- Laparoscopic spacer placement for bulky lymph node metastasis of cervical cancer: A case report.Gynecologic oncology reports · 2022Article
- Demonstrating the benefits of corrective intraoperative feedback in improving the quality of duodenal hydrogel spacer placement.Medical physics · 2022Article
- A phantom-based analysis for tracking intra-fraction pancreatic tumor motion by ultrasound imaging during radiation therapy.Frontiers in oncology · 2022Article
- Finite Element-Based Personalized Simulation of Duodenal Hydrogel Spacer: Spacer Location Dependent Duodenal Sparing and a Decision Support System for Spacer-Enabled Pancreatic Cancer Radiation Therapy.Frontiers in oncology · 2022Article
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6 authors.
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Abstract
purposeWe proposed a Haar feature-based method for tracking endoscopic ultrasound (EUS) probe in diagnostic computed tomography (CT) and Magnetic Resonance Imaging (MRI) scans for guiding hydrogel injection without external tracking hardware. This study aimed to assess the feasibility of implementing our method with phantom and patient images. MATERIALS AND
methodsOur methods included the pre-simulation section and Haar features extraction steps. Firstly, the simulated EUS set was generated based on anatomic information of interpolated CT/MRI images. Secondly, the efficient Haar features were extracted from simulated EUS images to create a Haar feature dictionary. The relative EUS probe position was estimated by searching the best matched Haar feature vector of the dictionary with Haar feature vector of target EUS images. The utilization of this method was validated using EUS phantom and patient CT/MRI images.
resultsIn the phantom experiment, we showed that our Haar feature-based EUS probe tracking method can find the best matched simulated EUS image from a simulated EUS dictionary which includes 123 simulated images. The errors of all four target points between the real EUS image and the best matched EUS images were within 1 mm. In the patient CT/MRI scans, the best matched simulated EUS image was selected by our method accurately, thereby confirming the probe location. However, when applying our method in MRI images, our method is not always robust due to the low image resolution.
conclusionsOur Haar feature-based method is capable to find the best matched simulated EUS image from the dictionary. We demonstrated the feasibility of our method for tracking EUS probe without external tracking hardware, thereby guiding the hydrogel injection between the head of the pancreas and duodenum.
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