cone beam computed tomography
PulseAugur coverage of cone beam computed tomography — every cluster mentioning cone beam computed tomography across labs, papers, and developer communities, ranked by signal.
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New framework generates dental CBCT reports from incomplete data
Researchers have developed EviDent-CBCT, a novel framework for generating reports from dental cone-beam CT scans, particularly when clinical data is incomplete. This system addresses the challenge of non-exhaustive repo…
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TotalSynth framework generates synthetic CT from MRI and CBCT scans
Researchers have developed TotalSynth, a framework capable of generating synthetic CT images from MRI and CBCT scans. The system was evaluated on a dataset comprising SynthRAD challenge data and multiple prostate cohort…
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New AI system TeethGNN automates malocclusion grading from CBCT scans
Researchers have developed TeethGNN, a novel graph-based framework for automatically grading malocclusion from cone-beam computed tomography (CBCT) images. This system bypasses the need for manual measurements by direct…
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New framework enables 3D CBCT segmentation with unsupervised CT model adaptation
Researchers have developed a new unsupervised domain adaptation framework to improve 3D segmentation of cone-beam CT (CBCT) scans. This method addresses the challenges of limited annotated CBCT data and the significant …
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New framework improves low-resource dental record completion from CBCT scans
Researchers have developed a new framework called Entity-Constrained CBCT-Guided Retrieval (ECCR) to improve the completion of dental records from cone-beam computed tomography (CBCT) scans, particularly in low-resource…
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Persistent homology boosts accuracy in dental imaging analysis
Researchers have developed a novel approach using persistent homology, a topological data analysis technique, to automate tasks in dental imaging from cone beam computed tomography (CBCT) scans. This method, combined wi…
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CephViT model automates cephalometric landmark localization for malocclusion classification
Researchers have developed CephViT, a Vision Transformer model designed for automated 2D lateral cephalometric landmark localization. This model was trained and evaluated on a public dataset, achieving a mean radial err…
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New splat-based method reduces metal artifacts in CT scans
Researchers have developed a new method for reducing artifacts in cone-beam computed tomography (CBCT) scans, particularly those caused by metal implants. This novel approach utilizes a physics-inspired, self-calibratin…
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New APCReg framework improves CBCT-IOS registration for surgical planning
Researchers have developed APCReg, a novel framework for registering cone-beam computed tomography (CBCT) with intraoral scans (IOS). This method addresses challenges posed by disparate imaging modalities and potential …
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AI synthesizes CT-equivalent images from low-dose scans for radiotherapy
Researchers have developed a deep learning framework using a conditional denoising diffusion probabilistic model to synthesize CT-equivalent images from low-dose cone-beam CT (CBCT) scans. This approach aims to improve …
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New diffusion model synthesizes high-quality CT images from CBCT scans
Researchers have developed a novel diffusion-based conditional generative model, named EqDiff-CT, designed to synthesize high-quality computed tomography (CT) images from cone-beam computed tomography (CBCT) scans. This…
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Differentiable SV-FBP for Cone-Beam CT Shows Robustness to Trajectory Irregularities
Researchers have analyzed the Differentiable Shift-Variant FBP (SV-FBP) framework for cone-beam CT reconstruction, finding it robust to irregular and discontinuous source trajectories. The framework's performance is mor…
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New framework redefines intraoperative CBCT from data completeness to sufficiency
This review paper proposes a new framework for intraoperative cone-beam computed tomography (CBCT) that shifts focus from "data completeness" to "data sufficiency." The authors argue that achieving mathematically comple…
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WING generative network achieves SOTA CT synthesis from MRI/CBCT · 3 sources tracked
Researchers have developed WING, a novel generative network designed for cross-modality CT synthesis. This model reformulates the regression target into multiple windowed representations, addressing challenges with dire…
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X-Splat uses Gaussian Splatting for 3D dental imaging from single X-rays
Researchers have developed X-Splat, a novel framework utilizing Gaussian splatting to generate 3D cone-beam computed tomography (CBCT) dental volumes from a single panoramic radiograph. This method addresses the underde…
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New framework generates synthetic projection images from transformed anatomical scenes
Researchers have developed a new framework for generating synthetic projection images from complex anatomical scenes, particularly focusing on scenarios involving spatial transformations like mandibular motion. This met…
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New framework quantifies radiation dose uncertainty in cervical cancer therapy
Researchers have developed IMPACT-DoseAcc, a new framework for estimating cumulative radiation dose in adaptive radiotherapy (ART) for cervical cancer. This system quantifies uncertainties arising from image registratio…
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Self-supervised vision transformers show promise for TMJ OA detection
Researchers have explored the effectiveness of self-supervised vision transformers, specifically the DINO family, for detecting temporomandibular joint osteoarthritis (TMJ OA) from cone-beam CT (CBCT) scans. Their study…
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New navigation system enhances femoral osteotomy accuracy
Researchers have developed a new electromagnetic tracking (EMT)-based navigation system for femoral osteotomies, aiming to improve accuracy and reduce radiation exposure. The system integrates CT-based planning with a s…
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New diffusion model enhances CT image synthesis with physics consistency
Researchers have developed EPC-3D-Diff, a new conditional 3D latent diffusion model designed to improve the synthesis of CT images from CBCT data. This model incorporates a physics-derived equivariance loss that ensures…