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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 726–750 of 1207 papers

TitleStatusHype
Solving Low-Dose CT Reconstruction via GAN with Local Coherence—0
Sparse2Inverse: Self-supervised inversion of sparse-view CT data—0
Sparse and redundant signal representations for x-ray computed tomography—0
3DGR-CT: Sparse-View CT Reconstruction with a 3D Gaussian Representation—0
Sparse-View Spectral CT Reconstruction Using Deep Learning—0
Sparse-View X-Ray CT Reconstruction Using _1 Prior with Learned Transform—0
Spatial Aggregation of Holistically-Nested Convolutional Neural Networks for Automated Pancreas Localization and Segmentation—0
Spatiotemporal Feature Learning Based on Two-Step LSTM and Transformer for CT Scans—0
Spatio-Temporal Hybrid Fusion of CAE and SWIn Transformers for Lung Cancer Malignancy Prediction—0
Spatio-Temporal Split Learning for Privacy-Preserving Medical Platforms: Case Studies with COVID-19 CT, X-Ray, and Cholesterol Data—0
Spiral Contrastive Learning: An Efficient 3D Representation Learning Method for Unannotated CT Lesions—0
SS-CTML: Self-Supervised Cross-Task Mutual Learning for CT Image Reconstruction—0
Stabilizing Deep Tomographic Reconstruction—0
Stabilizing dual-energy X-ray computed tomography reconstructions using patch-based regularization—0
Stagnant zone segmentation with U-net—0
Stationary Multi-source AI-powered Real-time Tomography (SMART)—0
Statistical models and regularization strategies in statistical image reconstruction of low-dose X-ray CT: a survey—0
Stochastic Primal-Dual Deep Unrolling—0
Stochastic tissue window normalization of deep learning on computed tomography—0
Stroke lesion detection using convolutional neural networks—0
Strong Baseline and Bag of Tricks for COVID-19 Detection of CT Scans—0
Structurally aware bidirectional unpaired image to image translation between CT and MR—0
Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising—0
StyleGAN2-based Out-of-Distribution Detection for Medical Imaging—0
Super-Resolution and Sparse View CT Reconstruction—0
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