ArticlePhysics in medicine and biology2018
Low dose CBCT reconstruction via prior contour based total variation (PCTV) regularization: a feasibility study.
Article in Physics in medicine and biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Prior Image-Guided Adaptive-Weighted Relative Total Variation for Sparse-View Computed Laminography of Plate-like Objects.Sensors (Basel, Switzerland) · 2026Article
- Fast four-dimensional cone-beam computed tomography reconstruction using deformable convolutional networks.Medical physics · 2022Article
- Structurally-constrained optical-flow-guided adversarial generation of synthetic CT for MR-only radiotherapy treatment planning.Scientific reports · 2022Article
- A geometry-guided multi-beamlet deep learning technique for CT reconstruction.Biomedical physics & engineering express · 2022Article
- A cycle generative adversarial network for improving the quality of four-dimensional cone-beam computed tomography images.Radiation oncology (London, England) · 2022Article
- Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis.Physics in medicine and biology · 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
- Prior image-guided cone-beam computed tomography augmentation from under-sampled projections using a convolutional neural network.Quantitative imaging in medicine and surgery · 2021Article
- A geometry-guided deep learning technique for CBCT reconstruction.Physics in medicine and biology · 2021Article
- A generative adversarial network (GAN)-based technique for synthesizing realistic respiratory motion in the extended cardiac-torso (XCAT) phantoms.Physics in medicine and biology · 2021Article
- 4D radiomics: impact of 4D-CBCT image quality on radiomic analysis.Physics in medicine and biology · 2021Article
- Low-dose cone-beam CT (LD-CBCT) reconstruction for image-guided radiation therapy (IGRT) by three-dimensional dual-dictionary learning.Radiation oncology (London, England) · 2020Article
- Development of realistic multi-contrast textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN).Physics in medicine and biology · 2020Article
- Augmentation of CBCT Reconstructed From Under-Sampled Projections Using Deep Learning.IEEE transactions on medical imaging · 2019Article
- Daily edge deformation prediction using an unsupervised convolutional neural network model for low dose prior contour based total variation CBCT reconstruction (PCTV-CNN).Biomedical physics & engineering express · 2019Article
- Low dose cone-beam computed tomography reconstruction via hybrid prior contour based total variation regularization (hybrid-PCTV).Quantitative imaging in medicine and surgery · 2019Article
- Low dose CBCT reconstruction via prior contour based total variation (PCTV) regularization: a feasibility study.Physics in medicine and biology · 2018Article
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5 authors.
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Abstract
purposecompressed sensing reconstruction using total variation (TV) tends to over-smooth the edge information by uniformly penalizing the image gradient. The goal of this study is to develop a novel prior contour based TV (PCTV) method to enhance the edge information in compressed sensing reconstruction for CBCT.
methodsthe edge information is extracted from prior planning-CT via edge detection. Prior CT is first registered with on-board CBCT reconstructed with TV method through rigid or deformable registration. The edge contours in prior-CT is then mapped to CBCT and used as the weight map for TV regularization to enhance edge information in CBCT reconstruction. The PCTV method was evaluated using extended-cardiac-torso (XCAT) phantom, physical CatPhan phantom and brain patient data. Results were compared with both TV and edge preserving TV (EPTV) methods which are commonly used for limited projection CBCT reconstruction. Relative error was used to calculate pixel value difference and edge cross correlation was defined as the similarity of edge information between reconstructed images and ground truth in the quantitative evaluation.
resultscompared to TV and EPTV, PCTV enhanced the edge information of bone, lung vessels and tumor in XCAT reconstruction and complex bony structures in brain patient CBCT. In XCAT study using 45 half-fan CBCT projections, compared with ground truth, relative errors were 1.5%, 0.7% and 0.3% and edge cross correlations were 0.66, 0.72 and 0.78 for TV, EPTV and PCTV, respectively. PCTV is more robust to the projection number reduction. Edge enhancement was reduced slightly with noisy projections but PCTV was still superior to other methods. PCTV can maintain resolution while reducing the noise in the low mAs CatPhan reconstruction. Low contrast edges were preserved better with PCTV compared with TV and EPTV.
conclusionPCTV preserved edge information as well as reduced streak artifacts and noise in low dose CBCT reconstruction. PCTV is superior to TV and EPTV methods in edge enhancement, which can potentially improve the localization accuracy in radiation therapy.
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