TY - JOUR
T1 - The Feasibility of Haar Feature-Based Endoscopic Ultrasound Probe Tracking for Implanting Hydrogel Spacer in Radiation Therapy for Pancreatic Cancer
AU - Feng, Ziwei
AU - Hooshangnejad, Hamed
AU - Shin, Eun Ji
AU - Narang, Amol
AU - Lediju Bell, Muyinatu A.
AU - Ding, Kai
N1 - Funding Information:
The authors would like to thank the staff of the Carnegie Center for Surgical Innovation at Johns Hopkins University for their valuable assistance, Denise Link-Farajali (Center for Leadership education at Johns Hopkins University) for the English language consultation, and Xinyue Huang for productive advice, and the anonymous reviewers for their helpful comments.
Funding Information:
Research reported in this publication was supported by the National Institutes of Health (award numbers R37CA229417).
Publisher Copyright:
© Copyright © 2021 Feng, Hooshangnejad, Shin, Narang, Lediju Bell and Ding.
PY - 2021/11/4
Y1 - 2021/11/4
N2 - Purpose: We 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 Methods: Our 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. Results: In 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. Conclusions: Our 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.
AB - Purpose: We 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 Methods: Our 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. Results: In 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. Conclusions: Our 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.
KW - Haar feature
KW - endoscopic ultrasound (EUS)
KW - hydrogel spacer
KW - pancreatic cancer
KW - probe tracking
KW - radiation therapy
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U2 - 10.3389/fonc.2021.759811
DO - 10.3389/fonc.2021.759811
M3 - Article
C2 - 34804959
AN - SCOPUS:85119416063
SN - 2234-943X
VL - 11
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 759811
ER -