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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 651–675 of 1207 papers

TitleStatusHype
Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation—0
Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration—0
Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study—0
Stationary Multi-source AI-powered Real-time Tomography (SMART)—0
Deep learning based dictionary learning and tomographic image reconstruction—0
Spatio-Temporal Split Learning for Privacy-Preserving Medical Platforms: Case Studies with COVID-19 CT, X-Ray, and Cholesterol Data—0
A Flexible Three-Dimensional Hetero-phase Computed Tomography Hepatocellular Carcinoma (HCC) Detection Algorithm for Generalizable and Practical HCC Screening—0
MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions—0
Resetting the baseline: CT-based COVID-19 diagnosis with Deep Transfer Learning is not as accurate as widely thought—0
Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning—0
FL-MISR: Fast Large-Scale Multi-Image Super-Resolution for Computed Tomography Based on Multi-GPU Acceleration—0
PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images—0
AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo—0
Uncertainty-Based Dynamic Graph Neighborhoods For Medical SegmentationCode0
Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting—0
Technical Report: Quality Assessment Tool for Machine Learning with Clinical CTCode0
Modality-aware Mutual Learning for Multi-modal Medical Image SegmentationCode1
Update 3.0 to “PuMA: The Porous Microstructure Analysis software”Code1
RECIST-Net: Lesion detection via grouping keypoints on RECIST-based annotation—0
Frequency-Supervised MR-to-CT Image SynthesisCode0
Zero-Shot Domain Adaptation in CT Segmentation by Filtered Back Projection AugmentationCode0
Medical Imaging with Deep Learning for COVID- 19 Diagnosis: A Comprehensive Review—0
Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms—0
Visual Transformer with Statistical Test for COVID-19 Classification—0
Training of deep cross-modality conversion models with a small dataset, and their application in megavoltage CT to kilovoltage CT conversion—0
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