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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 801–825 of 1207 papers

TitleStatusHype
Highly accurate model for prediction of lung nodule malignancy with CT scans—0
High-quality Low-dose CT Reconstruction Using Convolutional Neural Networks with Spatial and Channel Squeeze and Excitation—0
High-risk Factor Prediction in Lung Cancer Using Thin CT Scans: An Attention-Enhanced Graph Convolutional Network Approach—0
Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling—0
Holographic Visualisation of Radiology Data and Automated Machine Learning-based Medical Image Segmentation—0
How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?—0
HResFormer: Hybrid Residual Transformer for Volumetric Medical Image Segmentation—0
Human Recognition Using Face in Computed Tomography—0
Human Treelike Tubular Structure Segmentation: A Comprehensive Review and Future Perspectives—0
Hybrid deep convolution model for lung cancer detection with transfer learning—0
IDOL-Net: An Interactive Dual-Domain Parallel Network for CT Metal Artifact Reduction—0
Image Prediction for Limited-angle Tomography via Deep Learning with Convolutional Neural Network—0
Image Reconstruction by Splitting Expectation Propagation Techniques from Iterative Inversion—0
Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning—0
Imitating Radiological Scrolling: A Global-Local Attention Model for 3D Chest CT Volumes Multi-Label Anomaly Classification—0
Implanting Synthetic Lesions for Improving Liver Lesion Segmentation in CT Exams—0
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction—0
Improve Cross-Modality Segmentation by Treating T1-Weighted MRI Images as Inverted CT Scans—0
Improved Material Decomposition with a Two-step Regularization for spectral CT—0
Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study—0
Improving Automated Hemorrhage Detection in Sparse-view Computed Tomography via Deep Convolutional Neural Network based Artifact Reduction—0
Improving Cone-Beam CT Image Quality with Knowledge Distillation-Enhanced Diffusion Model in Imbalanced Data Settings—0
Improving mesh-based motion compensation by using edge adaptive graph-based compensated wavelet lifting for medical data sets—0
Improving Vertebra Segmentation through Joint Vertebra-Rib Atlases—0
INeAT: Iterative Neural Adaptive Tomography—0
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