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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 251–275 of 1207 papers

TitleStatusHype
Classification of lung cancer subtypes on CT images with synthetic pathological priors—0
Classification of lung nodules in CT images based on Wasserstein distance in differential geometry—0
A Novel Automated Classification and Segmentation for COVID-19 using 3D CT Scans—0
Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations—0
Active Learning on Medical Image—0
COVID-19 CT Image Synthesis with a Conditional Generative Adversarial Network—0
Novel coronavirus pneumonia lesion segmentation in CT images—0
Automatic segmentation of kidney and liver tumors in CT images—0
Active CT Reconstruction with a Learned Sampling Policy—0
Automatic segmentation and determining radiodensity of the liver in a large-scale CT database—0
Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities—0
A Lightweight Structure Aimed to Utilize Spatial Correlation for Sparse-View CT Reconstruction—0
A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT—0
Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection—0
A Lightweight Dual-Domain Attention Framework for Sparse-View CT Reconstruction—0
A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning—0
Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge—0
Automatic Lung Cancer Prediction from Chest X-ray Images Using Deep Learning Approach—0
Algorithm-driven Advances for Scientific CT Instruments: From Model-based to Deep Learning-based Approaches—0
Iterative CT Reconstruction via Latent Variable Optimization of Shallow Diffusion Models—0
Covid-19 classification with deep neural network and belief functions—0
COVID-19 Detection in Computed Tomography Images with 2D and 3D Approaches—0
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios—0
COVID CT-Net: Predicting Covid-19 From Chest CT Images Using Attentional Convolutional Network—0
Automatic Lumbar Spinal CT Image Segmentation with a Dual Densely Connected U-Net—0
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