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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 701–750 of 1207 papers

TitleStatusHype
Segmentation Criteria in the Problem of Porosity Determination based on CT Scans—0
Segmentation of Aortic Vessel Tree in CT Scans with Deep Fully Convolutional Networks—0
Self-Attention Generative Adversarial Network for Iterative Reconstruction of CT Images—0
Self-distilled Masked Attention guided masked image modeling with noise Regularized Teacher (SMART) for medical image analysis—0
Self is the Best Learner: CT-free Ultra-Low-Dose PET Organ Segmentation via Collaborating Denoising and Segmentation Learning—0
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis—0
Self-Supervised Denoiser Framework—0
Self-Supervised Learning for Biological Sample Localization in 3D Tomographic Images—0
Self-Supervised Learning for Segmentation—0
Self-supervised Learning from 100 Million Medical Images—0
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
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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