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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
Fusing Medical Image Features and Clinical Features with Deep Learning for Computer-Aided Diagnosis—0
Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation—0
Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression from Chest CT ImagesCode1
Attention-Enhanced Cross-Task Network for Analysing Multiple Attributes of Lung Nodules in CT—0
Interpolation of CT Projections by Exploiting Their Self-Similarity and Smoothness—0
Coarse-to-fine Airway Segmentation Using Multi information Fusion Network and CNN-based Region Growing—0
Kernel-based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks—0
RCoNet: Deformable Mutual Information Maximization and High-order Uncertainty-aware Learning for Robust COVID-19 Detection—0
Classification of COVID-19 via Homology of CT-SCAN—0
Deep learning-based COVID-19 pneumonia classification using chest CT images: model generalizability—0
Noise Entangled GAN For Low-Dose CT Simulation—0
DAN-Net: Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact ReductionCode1
Boosting Deep Transfer Learning for COVID-19 Classification—0
Plug-and-Play gradient-based denoisers applied to CT image enhancementCode0
Detection and severity classification of COVID-19 in CT images using deep learning—0
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images—0
Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data—0
A multiscale model of vascular function in chronic thromboembolic pulmonary hypertension—0
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention MechanismCode1
A Real-World Demonstration of Machine Learning Generalizability: Intracranial Hemorrhage Detection on Head CT—0
Multi-Label Annotation of Chest Abdomen Pelvis Computed Tomography Text Reports Using Deep LearningCode0
Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted LossCode1
Few-shot Learning for CT Scan based COVID-19 Diagnosis—0
A fast method for simultaneous reconstruction and segmentation in X-ray CT application—0
Automated femur segmentation from computed tomography images using a deep neural network—0
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