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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 1051–1075 of 1207 papers

TitleStatusHype
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data—0
Conditioning Generative Latent Optimization for Sparse-View CT Image Reconstruction—0
Conformal Risk Control for Semantic Uncertainty Quantification in Computed Tomography—0
Constraint-Based Model in Multimodal Learning to Improve Ventricular Arrhythmia Prediction—0
Context-aware PolyUNet for Liver and Lesion Segmentation from Abdominal CT Images—0
Context Driven Label Fusion for segmentation of Subcutaneous and Visceral Fat in CT Volumes—0
Continuous Filtered Backprojection by Learnable Interpolation Network—0
Continuous Learned Primal Dual—0
Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery—0
Contrast Phase Classification with a Generative Adversarial Network—0
Controlling Neural Networks via Energy Dissipation—0
Convolutional Neural Networks for Segmentation of Malignant Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance)—0
Domain specific cues improve robustness of deep learning based segmentation of ct volumes—0
Convolutional Sparse Coding for Compressed Sensing CT Reconstruction—0
Convolutional Sparse Support Estimator Based Covid-19 Recognition from X-ray Images—0
COPD Classification in CT Images Using a 3D Convolutional Neural Network—0
Coronary artery segmentation in non-contrast calcium scoring CT images using deep learning—0
Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods—0
COSST: Multi-organ Segmentation with Partially Labeled Datasets Using Comprehensive Supervisions and Self-training—0
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection—0
Counterfactuals and Uncertainty-Based Explainable Paradigm for the Automated Detection and Segmentation of Renal Cysts in Computed Tomography Images: A Multi-Center Study—0
Cov3d: Detection of the presence and severity of COVID-19 from CT scans using 3D ResNets—0
COVID-19 Chest CT Image Segmentation -- A Deep Convolutional Neural Network Solution—0
Covid-19 classification with deep neural network and belief functions—0
COVID-19 CT Image Synthesis with a Conditional Generative Adversarial Network—0
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