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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 976–1000 of 1207 papers

TitleStatusHype
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric UncertaintyCode0
Liver Segmentation from Multimodal Images using HED-Mask R-CNN—0
Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT—0
Automatic Lumbar Spinal CT Image Segmentation with a Dual Densely Connected U-Net—0
Organ At Risk Segmentation with Multiple Modality—0
Segmentation Criteria in the Problem of Porosity Determination based on CT Scans—0
Improved Material Decomposition with a Two-step Regularization for spectral CT—0
Extreme Few-view CT Reconstruction using Deep Inference—0
A Deep Learning System That Generates Quantitative CT Reports for Diagnosing Pulmonary Tuberculosis—0
1-point RANSAC for Circular Motion Estimation in Computed Tomography (CT)—0
Function Follows Form: Regression from Complete Thoracic Computed Tomography Scans—0
Optimal Transport driven CycleGAN for Unsupervised Learning in Inverse Problems—0
Deep-learning-based Breast CT for Radiation Dose Reduction—0
Invasiveness Prediction of Pulmonary Adenocarcinomas Using Deep Feature Fusion Networks—0
Learning to Avoid Poor Images: Towards Task-aware C-arm Cone-beam CT Trajectories—0
Z-Net: an Anisotropic 3D DCNN for Medical CT Volume Segmentation—0
Efficient 3D Fully Convolutional Networks for Pulmonary Lobe Segmentation in CT ImagesCode0
Local block-wise self attention for normal organ segmentation—0
MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion DetectionCode0
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms—0
Integrating Data and Image Domain Deep Learning for Limited Angle Tomography using Consensus Equilibrium—0
3D Anchor-Free Lesion Detector on Computed Tomography Scans—0
Are Quantitative Features of Lung Nodules Reproducible at Different CT Acquisition and Reconstruction Parameters?—0
Shape-Aware Complementary-Task Learning for Multi-Organ SegmentationCode0
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and SegmentationCode0
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