scholarly journals Patient-specific minimum-dose imaging protocols for statistical image reconstruction in C-arm cone-beam CT using correlated noise injection

2014 ◽  
Author(s):  
A. S. Wang ◽  
J. W. Stayman ◽  
Y. Otake ◽  
A. J. Khanna ◽  
G. L. Gallia ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Patient Specific ◽  
Correlated Noise ◽  
Minimum Dose ◽  
Statistical Image Reconstruction ◽  
Imaging Protocols ◽  
Noise Injection ◽  
Dose Imaging

Task-based statistical image reconstruction for high-quality cone-beam CT

2017 ◽  
Vol 62 (22) ◽  
pp. 8693-8719 ◽  
Author(s):  
Hao Dang ◽  
J Webster Stayman ◽  
Jennifer Xu ◽  
Wojciech Zbijewski ◽  
Alejandro Sisniega ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
High Quality ◽  
Statistical Image Reconstruction

scholarly journals Multi-resolution statistical image reconstruction for mitigation of truncation effects: application to cone-beam CT of the head

2016 ◽  
Vol 62 (2) ◽  
pp. 539-559 ◽  
Author(s):  
Hao Dang ◽  
J Webster Stayman ◽  
Alejandro Sisniega ◽  
Wojciech Zbijewski ◽  
Jennifer Xu ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Statistical Image Reconstruction

scholarly journals CBCT imaging: a simple approach for optimising and evaluating concomitant imaging doses, based on patient-specific attenuation, during radiotherapy pelvis treatment

2021 ◽  
Vol 94 (1124) ◽  
pp. 20210068
Author(s):  
Caroline Ordóñez-Sanz ◽  
Mark Cowen ◽  
Neda Shiravand ◽  
Niall D MacDougall
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Patient Specific ◽  
Specific Attenuation ◽  
Imaging Protocols ◽  
Phantom Measurements ◽  
Organ At Risk ◽  
Imaging Dose ◽  
Planning Ct ◽  
Dose Reductions

Objectives: A simple, robust method, for optimising cone-beam CT (CBCT) dose and image quality for pelvis treatment, based on patient-specific attenuation. Methods: Methods were investigated for grouping patients into four imaging categories (small [S], medium [M], large [L], extra large [XL]), based on planning-CT CTDIvol, and phantoms constructed to represent each group. CBCTs with varying kV, mA and ms honed in on the best settings, with a bladder noise of 25 HU. A patient pilot study clinically verified the new imaging settings. Results: The planning CTDIvol is a reliable method for grouping patients. Phantom measurements from the S, M and L groups show doses significantly reduced (19–83% reduction), whilst the XL group required an increase of 39%. Phantom TLD measurements showed the number of scans needed to increase rectal organ at risk (OAR) dose by 1 Gy was 143 (S group) and 50 (M group). Images were qualitatively assessed as sufficient by clinicians. Conclusion: Patient-specific CBCT modes are in use clinically with dose reductions across all modes except Pelvis XL, keeping doses ALARP and images optimal. Consideration of OAR doses controls the number of CBCTs allowed to ensure adherence to OAR tolerance. Reporting CBCT doses in “scans per Gray” allows clinicians to make informed decisions regarding the imaging schedule and concomitant doses. Advances in knowledge: Patient grouping at planning CT, using CTDIvol, allows for CBCT imaging protocols to be selected based on patient specific attenuation. Reporting OAR doses in terms of “scans per Gray” allows translation of imaging dose risk to the Oncologist.

scholarly journals Soft-tissue imaging in low-dose, C-arm cone-beam CT using statistical image reconstruction

2013 ◽  
Author(s):  
Adam S. Wang ◽  
Sebastian Schafer ◽  
J. W. Stayman ◽  
Yoshi Otake ◽  
Marc S. Sussman ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Image Reconstruction ◽  
Low Dose ◽  
Cone Beam Ct ◽  
Tissue Imaging ◽  
Cone Beam ◽  
Statistical Image Reconstruction

Chord-based image reconstruction in cone-beam CT with a curved detector

2006 ◽  
Vol 33 (10) ◽  
pp. 3743-3757 ◽  
Author(s):  
Nianming Zuo ◽  
Dan Xia ◽  
Yu Zou ◽  
Tianzi Jiang ◽  
Xiao-Chuan Pan
Keyword(s):  
Image Reconstruction ◽  
Cone Beam Ct ◽  
Cone Beam

scholarly journals GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Xing Zhao ◽  
Jing-jing Hu ◽  
Peng Zhang
Keyword(s):  
Image Reconstruction ◽  
Cone Beam Ct ◽  
Large Data ◽  
Circular Cone ◽  
Cone Beam ◽  
Projection Data ◽  
Ct Image ◽  
Reconstruction Process ◽  
Data Volume ◽  
Ct Image Reconstruction

Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs) has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation.

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