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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 651–675 of 1207 papers

TitleStatusHype
Self-supervised learning improves robustness of deep learning lung tumor segmentation to CT imaging differences—0
Self-supervised Physics-based Denoising for Computed Tomography—0
Semantic Feature Attention Network for Liver Tumor Segmentation in Large-scale CT database—0
Semi-Automatic Segmentation of Autosomal Dominant Polycystic Kidneys using Random Forests—0
Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT—0
Semi-supervised Semantic Segmentation of Prostate and Organs-at-Risk on 3D Pelvic CT Images—0
Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images—0
Signed Distance Field based Segmentation and Statistical Shape Modelling of the Left Atrial Appendage—0
Single volume lung biomechanics from chest computed tomography using a mode preserving generative adversarial network—0
Sinogram constrained TV-minimization for metal artifact reduction in CT—0
Sinogram interpolation for sparse-view micro-CT with deep learning neural network—0
SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells—0
SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis—0
Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices—0
Solitary pulmonary nodules prediction for lung cancer patients using nomogram and machine learning—0
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
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