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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 576–600 of 1207 papers

TitleStatusHype
Deep learning and its application to medical image segmentation—0
Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration—0
Deep Inertia L_p Half-Quadratic Splitting Unrolling Network for Sparse View CT Reconstruction—0
Automatic Intracranial Brain Segmentation from Computed Tomography Head Images—0
Airway Tree Modeling Using Dual-channel 3D UNet 3+ with Vesselness Prior—0
Deep Ensembling with Multimodal Image Fusion for Efficient Classification of Lung Cancer—0
Deep Encoder-decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-view Data—0
Automatic Diagnosis of COVID-19 from CT Images using CycleGAN and Transfer Learning—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
A convergence proof of the split Bregman method for regularized least-squares problems—0
4D VQ-GAN: Synthesising Medical Scans at Any Time Point for Personalised Disease Progression Modelling of Idiopathic Pulmonary Fibrosis—0
Deep convolutional networks for pancreas segmentation in CT imaging—0
Automatic 3D liver location and segmentation via convolutional neural networks and graph cut—0
Deep Clustering Activation Maps for Emphysema Subtyping—0
Deep Boosted Regression for MR to CT Synthesis—0
Automated Tumor Segmentation and Brain Mapping for the Tumor Area—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Automated triage of COVID-19 from various lung abnormalities using chest CT features—0
Deciphering scrolls with tomography: A training experiment—0
Automated Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction—0
AI-Powered Intracranial Hemorrhage Detection: A Co-Scale Convolutional Attention Model with Uncertainty-Based Fuzzy Integral Operator and Feature Screening—0
DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding—0
Automated segmentation of 3-D body composition on computed tomography—0
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images—0
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