ArticleMedical physics2017
Estimating 4D-CBCT from prior information and extremely limited angle projections using structural PCA and weighted free-form deformation for lung radiotherapy.
Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- A review on 4D cone-beam CT (4D-CBCT) in radiation therapy: Technical advances and clinical applications.Medical physics · 2024Review
- Dynamic cone-beam CT reconstruction using spatial and temporal implicit neural representation learning (STINR).Physics in medicine and biology · 2023Article
- Real-time Markerless Tracking of Lung Tumors based on 2-D Fluoroscopy Imaging using Convolutional LSTM.IEEE transactions on radiation and plasma medical sciences · 2022Article
- Enhancement of 4-D Cone-Beam Computed Tomography (4D-CBCT) Using a Dual-Encoder Convolutional Neural Network (DeCNN).IEEE transactions on radiation and plasma medical sciences · 2022Article
- Multi-contrast four-dimensional magnetic resonance imaging (MC-4D-MRI): Development and initial evaluation in liver tumor patients.Medical physics · 2021Article
- Prior image-guided cone-beam computed tomography augmentation from under-sampled projections using a convolutional neural network.Quantitative imaging in medicine and surgery · 2021Article
- Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model.Physics in medicine and biology · 2021Article
- Augmentation of CBCT Reconstructed From Under-Sampled Projections Using Deep Learning.IEEE transactions on medical imaging · 2019Article
- First clinical retrospective investigation of limited projection CBCT for lung tumor localization in patients receiving SBRT treatment.Physics in medicine and biology · 2019Article
- Advanced 4-dimensional cone-beam computed tomography reconstruction by combining motion estimation, motion-compensated reconstruction, biomechanical modeling and deep learning.Visual computing for industry, biomedicine, and art · 2019Article
- A Novel method to generate on-board 4D MRI using prior 4D MRI and on-board kV projections from a conventional LINAC for target localization in liver SBRT.Medical physics · 2018Article
- Low dose CBCT reconstruction via prior contour based total variation (PCTV) regularization: a feasibility study.Physics in medicine and biology · 2018Article
- Fast 4D cone-beam CT from 60 s acquisitions.Physics and imaging in radiation oncology · 2018Article
- Image acquisition optimization of a limited-angle intrafraction verification (LIVE) system for lung radiotherapy.Medical physics · 2018Article
- Reducing scan angle using adaptive prior knowledge for a limited-angle intrafraction verification (LIVE) system for conformal arc radiotherapy.Physics in medicine and biology · 2017Article
- Markerless Four-Dimensional-Cone Beam Computed Tomography Projection-Phase Sorting Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study.Cancer translational medicine · 2017Article
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Abstract
purposeTo investigate the feasibility of using structural-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy.
methodsA technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion model extracted by a global PCA and free-form deformation (GMM-FD) technique, using a data fidelity constraint and deformation energy minimization. In this study, a new structural PCA method was developed to build a structural motion model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respiratory changes from planning 4D-CT to on-board volume to evaluate the method. The estimation accuracy was evaluated by the volume percent difference (VPD)/center-of-mass-shift (COMS) between lesions in the estimated and "ground-truth" on-board 4D-CBCT. Different on-board projection acquisition scenarios and projection noise levels were simulated to investigate their effects on the estimation accuracy. The method was also evaluated against three lung patients.
resultsThe SMM-WFD method achieved substantially better accuracy than the GMM-FD method for CBCT estimation using extremely small scan angles or projections. Using orthogonal 15° scanning angles, the VPD/COMS were 3.47 ± 2.94% and 0.23 ± 0.22 mm for SMM-WFD and 25.23 ± 19.01% and 2.58 ± 2.54 mm for GMM-FD among all eight XCAT scenarios. Compared to GMM-FD, SMM-WFD was more robust against reduction of the scanning angles down to orthogonal 10° with VPD/COMS of 6.21 ± 5.61% and 0.39 ± 0.49 mm, and more robust against reduction of projection numbers down to only 8 projections in total for both orthogonal-view 30° and orthogonal-view 15° scan angles. SMM-WFD method was also more robust than the GMM-FD method against increasing levels of noise in the projection images. Additionally, the SMM-WFD technique provided better tumor estimation for all three lung patients compared to the GMM-FD technique.
conclusionCompared to the GMM-FD technique, the SMM-WFD technique can substantially improve the 4D-CBCT estimation accuracy using extremely small scan angles and low number of projections to provide fast low dose 4D target verification.
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