scholarly journals Technical Note: A method for quality assurance of landmark sets for use in evaluation of deformable image registration accuracy of lung parenchyma

2018 ◽  
Vol 46 (2) ◽  
pp. 766-773 ◽  
Author(s):  
Christopher L. Guy ◽  
Elisabeth Weiss ◽  
Nuzhat Jan ◽  
Gary E. Christensen ◽  
Geoffrey D. Hugo
Keyword(s):  
Quality Assurance ◽  
Image Registration ◽  
Deformable Image Registration ◽  
Lung Parenchyma ◽  
Technical Note ◽  
Registration Accuracy

scholarly journals Detection of vessel bifurcations in CT scans for automatic objective assessment of deformable image registration accuracy

2021 ◽  
Author(s):  
Guillaume Cazoulat ◽  
Brian M Anderson ◽  
Molly M McCulloch ◽  
Bastien Rigaud ◽  
Eugene J Koay ◽  
...  
Keyword(s):  
Image Registration ◽  
Objective Assessment ◽  
Deformable Image Registration ◽  
Ct Scans ◽  
Registration Accuracy ◽  
Vessel Bifurcations

scholarly journals Evaluation of a deformable image registration quality assurance tool for head and neck cancer patients

2020 ◽  
Vol 67 (4) ◽  
pp. 284-293 ◽  
Author(s):  
Molly Mee ◽  
Kate Stewart ◽  
Marika Lathouras ◽  
Helen Truong ◽  
Catriona Hargrave
Keyword(s):  
Quality Assurance ◽  
Head And Neck Cancer ◽  
Image Registration ◽  
Head And Neck ◽  
Cancer Patients ◽  
Neck Cancer ◽  
Deformable Image Registration

Multi‐atlas–based auto‐segmentation for prostatic urethra using novel prediction of deformable image registration accuracy

2020 ◽  
Vol 47 (7) ◽  
pp. 3023-3031
Author(s):  
Hisamichi Takagi ◽  
Noriyuki Kadoya ◽  
Tomohiro Kajikawa ◽  
Shohei Tanaka ◽  
Yoshiki Takayama ◽  
...  
Keyword(s):  
Image Registration ◽  
Deformable Image Registration ◽  
Prostatic Urethra ◽  
Registration Accuracy

Impact of deformable image registration accuracy on thoracic images with different regularization weight parameter settings

2017 ◽  
Vol 42 ◽  
pp. 108-111 ◽  
Author(s):  
Hideharu Miura ◽  
Shuichi Ozawa ◽  
Minoru Nakao ◽  
Kengo Furukawa ◽  
Yoshiko Doi ◽  
...  
Keyword(s):  
Image Registration ◽  
Deformable Image Registration ◽  
Registration Accuracy ◽  
Weight Parameter

scholarly journals Evaluation of Intensity- and Contour-Based Deformable Image Registration Accuracy in Pancreatic Cancer Patients

Cancers ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1447 ◽  
Author(s):  
Yoshiki Kubota ◽  
Masahiko Okamoto ◽  
Yang Li ◽  
Shintaro Shiba ◽  
Shohei Okazaki ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Image Registration ◽  
Prone Position ◽  
Supine Position ◽  
Deformable Image Registration ◽  
Pancreatic Cancer Patient ◽  
Target Volume ◽  
Ct Images ◽  
Registration Accuracy ◽  
Computed Tomography Images

We aimed to clarify the accuracy of rigid image registration and deformable image registration (DIR) in carbon-ion radiotherapy (CIRT) for pancreatic cancer. Six patients with pancreatic cancer who were treated with passive irradiation CIRT were enrolled. Three registration patterns were evaluated: treatment planning computed tomography images (TPCT) to CT images acquired in the treatment room (IRCT) in the supine position, TPCT to IRCT in the prone position, and TPCT in the supine position to the prone position. After warping the contours of the original CT images to the destination CT images using deformation matrices from the registration, the warped delineated contours on the destination CT images were compared with the original ones using mean displacement to agreement (MDA). Four contours (clinical target volume (CTV), gross tumor volume (GTV), stomach, duodenum) and four registration algorithms (rigid image registration [RIR], intensity-based DIR [iDIR], contour-based DIR [cDIR], and a hybrid iDIR-cDIR ([hDIR]) were evaluated. The means ± standard deviation of the MDAs of all contours for RIR, iDIR, cDIR, and hDIR were 3.40 ± 3.30, 2.2 1± 2.48, 1.46 ± 1.49, and 1.46 ± 1.37 mm, respectively. There were significant differences between RIR and iDIR, and between RIR/iDIR and cDIR/hDIR. For the pancreatic cancer patient images, cDIR and hDIR had better accuracy than RIR and iDIR.

Biomechanical quality assurance criteria for deformable image registration algorithms used in radiotherapy guidance

2020 ◽  
Vol 65 (1) ◽  
pp. 015006 ◽  
Author(s):  
Cornel Zachiu ◽  
Baudouin Denis de Senneville ◽  
Bas W Raaymakers ◽  
Mario Ries
Keyword(s):  
Quality Assurance ◽  
Image Registration ◽  
Deformable Image Registration

Quantitative Analysis Tools and Digital Phantoms for Deformable Image Registration Quality Assurance

2014 ◽  
Vol 14 (4) ◽  
pp. 428-439 ◽  
Author(s):  
Haksoo Kim ◽  
Samuel B. Park ◽  
James I. Monroe ◽  
Bryan J. Traughber ◽  
Yiran Zheng ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Quantitative Analysis ◽  
Image Registration ◽  
Deformable Image Registration ◽  
Analysis Tools ◽  
Digital Phantoms

scholarly journals Technical note: A novel boundary condition using contact elements for finite element based deformable image registration

2004 ◽  
Vol 31 (9) ◽  
pp. 2412-2415 ◽  
Author(s):  
Tiezhi Zhang ◽  
Nigel P. Orton ◽  
T. Rockwell Mackie ◽  
Bhudatt R. Paliwal
Keyword(s):  
Boundary Condition ◽  
Finite Element ◽  
Image Registration ◽  
Deformable Image Registration ◽  
Technical Note
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