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Computed Tomography (CT)

The term “computed tomography”, or CT, refers to a computerized x-ray imaging procedure in which a narrow beam of x-rays is aimed at a patient and quickly rotated around the body, producing signals that are processed by the machine's computer to generate cross-sectional images—or “slices”—of the body.

( Image credit: Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector )

Papers

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Showing 351–375 of 1207 papers

TitleStatusHype
Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation—0
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images—0
3D Anchor-Free Lesion Detector on Computed Tomography Scans—0
Deep Radon Prior: A Fully Unsupervised Framework for Sparse-View CT Reconstruction—0
Auto-Lesion Segmentation with a Novel Intensity Dark Channel Prior for COVID-19 Detection—0
Deep Sequential Learning for Cervical Spine Fracture Detection on Computed Tomography Imaging—0
AI generated annotations for Breast, Brain, Liver, Lungs and Prostate cancer collections in National Cancer Institute Imaging Data Commons—0
DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding—0
Cross-Modal Domain Adaptation in Brain Disease Diagnosis: Maximum Mean Discrepancy-based Convolutional Neural Networks—0
Deciphering scrolls with tomography: A training experiment—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Cross-domain Iterative Network for Simultaneous Denoising, Limited-angle Reconstruction, and Attenuation Correction of Low-dose Cardiac SPECT—0
Deep Boosted Regression for MR to CT Synthesis—0
Deep Clustering Activation Maps for Emphysema Subtyping—0
Automatic 3D liver location and segmentation via convolutional neural networks and graph cut—0
Deep convolutional networks for pancreas segmentation in CT imaging—0
Deep Embedding Convolutional Neural Network for Synthesizing CT Image from T1-Weighted MR Image—0
Automatic Airway Segmentation in chest CT using Convolutional Neural Networks—0
Deep Encoder-decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-view Data—0
Deep Ensembling with Multimodal Image Fusion for Efficient Classification of Lung Cancer—0
Automatic Intracranial Brain Segmentation from Computed Tomography Head Images—0
Deep Inertia L_p Half-Quadratic Splitting Unrolling Network for Sparse View CT Reconstruction—0
Deep learning and its application to medical image segmentation—0
Deep Learning Approach for Early Stage Lung Cancer Detection—0
AutoCT: Automated CT registration, segmentation, and quantification—0
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