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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 601–650 of 1207 papers

TitleStatusHype
Computational Scatter Correction for High-Resolution Flat-Panel CT Based on a Fast Monte Carlo Photon Transport Model—0
Lymphoma segmentation from 3D PET-CT images using a deep evidential networkCode1
A tomographic workflow to enable deep learning for X-ray based foreign object detectionCode0
Joint Liver and Hepatic Lesion Segmentation in MRI using a Hybrid CNN with Transformer Layers—0
Self-supervised Learning from 100 Million Medical Images—0
A Gradient Mapping Guided Explainable Deep Neural Network for Extracapsular Extension Identification in 3D Head and Neck Cancer Computed Tomography Images—0
Recurrent Feature Propagation and Edge Skip-Connections for Automatic Abdominal Organ Segmentation—0
Brain Signals Analysis Based Deep Learning Methods: Recent advances in the study of non-invasive brain signals—0
SECP-Net: SE-Connection Pyramid Network of Organ At Risk Segmentation for Nasopharyngeal Carcinoma—0
Event-based clinical findings extraction from radiology reports with pre-trained language modelCode0
Self-Attention Generative Adversarial Network for Iterative Reconstruction of CT Images—0
InDuDoNet+: A Deep Unfolding Dual Domain Network for Metal Artifact Reduction in CT ImagesCode1
ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral TomographyCode1
Automated segmentation of 3-D body composition on computed tomography—0
Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Images—0
Robust End-to-End Focal Liver Lesion Detection using Unregistered Multiphase Computed Tomography ImagesCode1
X-ray Dissectography Enables Stereotography to Improve Diagnostic Performance—0
Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image AnalysisCode1
RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR—0
DuDoTrans: Dual-Domain Transformer Provides More Attention for Sinogram Restoration in Sparse-View CT ReconstructionCode0
Evaluation of automated airway morphological quantification for assessing fibrosing lung diseaseCode1
Solving Inverse Problems in Medical Imaging with Score-Based Generative ModelsCode1
CodEx: A Modular Framework for Joint Temporal De-blurring and Tomographic Reconstruction—0
TomoSLAM: factor graph optimization for rotation angle refinement in microtomography—0
Detecting COVID-19 from Chest Computed Tomography Scans using AI-Driven Android Application—0
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style TransferCode1
Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A review—0
Novel coronavirus pneumonia lesion segmentation in CT images—0
"One-Shot" Reduction of Additive Artifacts in Medical Images—0
Cross-Vendor CT Image Data Harmonization Using CVH-CT—0
Stochastic Primal-Dual Deep Unrolling—0
GAN-based disentanglement learning for chest X-ray rib suppression—0
Body Part Regression for CT ImagesCode1
CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans—0
Comparing One-step and Two-step Scatter Correction and Density Reconstruction in X-ray CT—0
Single volume lung biomechanics from chest computed tomography using a mode preserving generative adversarial network—0
A Teacher-Student Framework with Fourier Augmentation for COVID-19 Infection Segmentation in CT Images—0
CyTran: A Cycle-Consistent Transformer with Multi-Level Consistency for Non-Contrast to Contrast CT TranslationCode1
AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation—0
Spark in the Dark: Evaluating Encoder-Decoder Pairs for COVID-19 CT's Semantic SegmentationCode0
Automated airway segmentation by learning graphical structure—0
Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense AttentionCode1
Improving Tuberculosis (TB) Prediction using Synthetically Generated Computed Tomography (CT) ImagesCode0
DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search—0
Asymmetric 3D Context Fusion for Universal Lesion DetectionCode0
RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT ScansCode0
DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CTCode1
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data—0
Unsupervised domain adaptation for cross-modality liver segmentation via joint adversarial learning and self-learningCode1
Leveraging Clinical Characteristics for Improved Deep Learning-Based Kidney Tumor Segmentation on CT—0
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