ArticleMedical physics2020
Cone-beam CT for imaging of the head/brain: Development and assessment of scanner prototype and reconstruction algorithms.
Article in Medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Joint Cone-Beam CT Reconstruction and Rigid Motion Compensation Using A Differentiable Projector.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Objective assessment of diagnostic image quality in CT scans: what radiologists and researchers need to know.Insights into imaging · 2025Review
- Evaluation of a compact cone beam CT concept with high image fidelity for point-of-care brain imaging.Scientific reports · 2024Article
- Vessel-targeted compensation of deformable motion in interventional cone-beam CT.Medical image analysis · 2024Article
- Deformable motion compensation in interventional cone-beam CT with a context-aware learned autofocus metric.Medical physics · 2024Article
- The effects of distance between the imaging isocenter and brain center on the image quality of cone-beam computed tomography for brain stereotactic irradiation.Physical and engineering sciences in medicine · 2024Article
- A quantitative CBCT pipeline based on 2D antiscatter grid and grid-based scatter sampling for image-guided radiation therapy.Medical physics · 2023Article
- Real-Time 3-D Video Reconstruction for Guidance of Transventricular Neurosurgery.IEEE transactions on medical robotics and bionics · 2023Article
- Cone-beam CT sampling incompleteness: analytical and empirical studies of emerging systems and source-detector orbits.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- The butterfly effect: improving brain cone-beam CT image artifacts for stroke assessment using a novel dual-axis trajectory.Journal of neurointerventional surgery · 2023Article
- Task-Driven CT Image Quality Optimization for Low-Contrast Lesion Detectability with Tunable Neural Networks.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Truncation effect reduction for fast iterative reconstruction in cone-beam CT.BMC medical imaging · 2022Article
- Reference-free learning-based similarity metric for motion compensation in cone-beam CT.Physics in medicine and biology · 2022Article
- Joint synthesis and registration network for deformable MR-CBCT image registration for neurosurgical guidance.Physics in medicine and biology · 2022Article
- Technical assessment of 2D and 3D imaging performance of an IGZO-based flat-panel X-ray detector.Medical physics · 2022Article
- Flat-panel conebeam CT in the clinic: history and current state.Journal of medical imaging (Bellingham, Wash.) · 2021Article
- Deformable motion compensation for interventional cone-beam CT.Physics in medicine and biology · 2021Article
- CBCT image quality QA: Establishing a quantitative program.Journal of applied clinical medical physics · 2020Article
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Authors and funding
10 authors.
Funding
Abstract
purposeOur aim was to develop a high-quality, mobile cone-beam computed tomography (CBCT) scanner for point-of-care detection and monitoring of low-contrast, soft-tissue abnormalities in the head/brain, such as acute intracranial hemorrhage (ICH). This work presents an integrated framework of hardware and algorithmic advances for improving soft-tissue contrast resolution and evaluation of its technical performance with human subjects.
methodsFour configurations of a CBCT scanner prototype were designed and implemented to investigate key aspects of hardware (including system geometry, antiscatter grid, bowtie filter) and technique protocols. An integrated software pipeline (c.f., a serial cascade of algorithms) was developed for artifact correction (image lag, glare, beam hardening and x-ray scatter), motion compensation, and three-dimensional image (3D) reconstruction [penalized weighted least squares (PWLS), with a hardware-specific statistical noise model]. The PWLS method was extended in this work to accommodate multiple, independently moving regions with different resolution (to address both motion compensation and image truncation). Imaging performance was evaluated quantitatively and qualitatively with 41 human subjects in the neurosciences critical care unit (NCCU) at our institution.
resultsThe progression of four scanner configurations exhibited systematic improvement in the quality of raw data by variations in system geometry (source-detector distance), antiscatter grid, and bowtie filter. Quantitative assessment of CBCT images in 41 subjects demonstrated: ~70% reduction in image nonuniformity with artifact correction methods (lag, glare, beam hardening, and scatter); ~40% reduction in motion-induced streak artifacts via the multi-motion compensation method; and ~15% improvement in soft-tissue contrast-to-noise ratio (CNR) for PWLS compared to filtered backprojection (FBP) at matched resolution. Each of these components was important to improve contrast resolution for point-of-care cranial imaging.
conclusionsThis work presents the first application of a high-quality, point-of-care CBCT system for imaging of the head/ brain in a neurological critical care setting. Hardware configuration iterations and an integrated software pipeline for artifacts correction and PWLS reconstruction mitigated artifacts and noise to achieve image quality that could be valuable for point-of-care detection and monitoring of a variety of intracranial abnormalities, including ICH and hydrocephalus.
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