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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 1076–1100 of 1207 papers

TitleStatusHype
COVID-19 Detection in Computed Tomography Images with 2D and 3D Approaches—0
COVID-19 Detection Using Slices Processing Techniques and a Modified Xception Classifier from Computed Tomography Images—0
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios—0
COVID-CLNet: COVID-19 Detection with Compressive Deep Learning Approaches—0
COVID CT-Net: Predicting Covid-19 From Chest CT Images Using Attentional Convolutional Network—0
CovidExpert: A Triplet Siamese Neural Network framework for the detection of COVID-19—0
COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans—0
Cross-dataset domain adaptation for the classification COVID-19 using chest computed tomography images—0
Cross-domain Iterative Network for Simultaneous Denoising, Limited-angle Reconstruction, and Attenuation Correction of Low-dose Cardiac SPECT—0
Cross-Modal Domain Adaptation in Brain Disease Diagnosis: Maximum Mean Discrepancy-based Convolutional Neural Networks—0
Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation—0
Cross-Vendor CT Image Data Harmonization Using CVH-CT—0
Crowdsourcing Lung Nodules Detection and Annotation—0
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering—0
CT-AGRG: Automated Abnormality-Guided Report Generation from 3D Chest CT Volumes—0
CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models—0
CTG-Net: An Efficient Cascaded Framework Driven by Terminal Guidance Mechanism for Dilated Pancreatic Duct Segmentation—0
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement—0
CT Image Harmonization for Enhancing Radiomics Studies—0
CT-image Super Resolution Using 3D Convolutional Neural Network—0
CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)—0
CT Super Resolution via Zero Shot Learning—0
Parallel Diffusion Model-based Sparse-view Cone-beam Breast CT—0
Cycle-free CycleGAN using Invertible Generator for Unsupervised Low-Dose CT Denoising—0
Cylindrical Transform: 3D Semantic Segmentation of Kidneys With Limited Annotated Images—0
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