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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 301–325 of 1207 papers

TitleStatusHype
AI generated annotations for Breast, Brain, Liver, Lungs and Prostate cancer collections in National Cancer Institute Imaging Data Commons—0
Automated segmentation of 3-D body composition on computed tomography—0
Deciphering scrolls with tomography: A training experiment—0
3D Anchor-Free Lesion Detector on Computed Tomography Scans—0
Automated recognition of the pericardium contour on processed CT images using genetic algorithms—0
DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Deep convolutional networks for pancreas segmentation in CT imaging—0
Automated pulmonary nodule detection using 3D deep convolutional neural networks—0
Automated processing of X-ray computed tomography images via panoptic segmentation for modeling woven composite textiles—0
AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia—0
Automated neuroradiological support systems for multiple cerebrovascular disease markers -- A systematic review and meta-analysis—0
Automated Methods for Detection and Classification Pneumonia based on X-Ray Images Using Deep Learning—0
AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo—0
A Computer-Aided Diagnosis System Using Artificial Intelligence for Hip Fractures -Multi-Institutional Joint Development Research-—0
Automated femur segmentation from computed tomography images using a deep neural network—0
A Hybrid Deep Learning CNN Model for Enhanced COVID-19 Detection from Computed Tomography (CT) Scan Images—0
3D U-Net for segmentation of COVID-19 associated pulmonary infiltrates using transfer learning: State-of-the-art results on affordable hardware—0
Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review—0
Automated COVID-19 CT Image Classification using Multi-head Channel Attention in Deep CNN—0
3D Aggregated Faster R-CNN for General Lesion Detection—0
Advancing Ischemic Stroke Diagnosis: A Novel Two-Stage Approach for Blood Clot Origin Identification—0
Automated airway segmentation by learning graphical structure—0
HRCTCov19 -- A High-Resolution Chest CT Scan Image Dataset for COVID-19 Diagnosis and Differentiation—0
Automated 5-year Mortality Prediction using Deep Learning and Radiomics Features from Chest Computed Tomography—0
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