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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 801–850 of 1207 papers

TitleStatusHype
Highly accurate model for prediction of lung nodule malignancy with CT scans—0
High-quality Low-dose CT Reconstruction Using Convolutional Neural Networks with Spatial and Channel Squeeze and Excitation—0
High-risk Factor Prediction in Lung Cancer Using Thin CT Scans: An Attention-Enhanced Graph Convolutional Network Approach—0
Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling—0
Holographic Visualisation of Radiology Data and Automated Machine Learning-based Medical Image Segmentation—0
How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?—0
HResFormer: Hybrid Residual Transformer for Volumetric Medical Image Segmentation—0
Human Recognition Using Face in Computed Tomography—0
Human Treelike Tubular Structure Segmentation: A Comprehensive Review and Future Perspectives—0
Hybrid deep convolution model for lung cancer detection with transfer learning—0
IDOL-Net: An Interactive Dual-Domain Parallel Network for CT Metal Artifact Reduction—0
Image Prediction for Limited-angle Tomography via Deep Learning with Convolutional Neural Network—0
Image Reconstruction by Splitting Expectation Propagation Techniques from Iterative Inversion—0
Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning—0
Imitating Radiological Scrolling: A Global-Local Attention Model for 3D Chest CT Volumes Multi-Label Anomaly Classification—0
Implanting Synthetic Lesions for Improving Liver Lesion Segmentation in CT Exams—0
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction—0
Improve Cross-Modality Segmentation by Treating T1-Weighted MRI Images as Inverted CT Scans—0
Improved Material Decomposition with a Two-step Regularization for spectral CT—0
Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study—0
Improving Automated Hemorrhage Detection in Sparse-view Computed Tomography via Deep Convolutional Neural Network based Artifact Reduction—0
Improving Cone-Beam CT Image Quality with Knowledge Distillation-Enhanced Diffusion Model in Imbalanced Data Settings—0
Improving mesh-based motion compensation by using edge adaptive graph-based compensated wavelet lifting for medical data sets—0
Improving Vertebra Segmentation through Joint Vertebra-Rib Atlases—0
INeAT: Iterative Neural Adaptive Tomography—0
Inertial Measurements for Motion Compensation in Weight-bearing Cone-beam CT of the Knee—0
Integer Optimization of CT Trajectories using a Discrete Data Completeness Formulation—0
Integrating Data and Image Domain Deep Learning for Limited Angle Tomography using Consensus Equilibrium—0
Integrating Deep Unfolding with Direct Diffusion Bridges for Computed Tomography Reconstruction—0
Integrating features from lymph node stations for metastatic lymph node detection—0
Interactive segmentation of medical images through fully convolutional neural networks—0
Interpolation of CT Projections by Exploiting Their Self-Similarity and Smoothness—0
Interpretable 3D Multi-Modal Residual Convolutional Neural Network for Mild Traumatic Brain Injury Diagnosis—0
Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images—0
Interpretable Auto Window Setting for Deep-Learning-Based CT Analysis—0
Interpretable Geoscience Artificial Intelligence (XGeoS-AI): Application to Demystify Image Recognition—0
Inter-vendor harmonization of Computed Tomography (CT) reconstruction kernels using unpaired image translation—0
Intracranial Hemorrhage Detection Using Neural Network Based Methods With Federated Learning—0
Introduction of Medical Imaging Modalities—0
Ischemic Stroke Lesion Segmentation Using Adversarial Learning—0
Fast and Stable Diffusion Inverse Solver with History Gradient Update—0
Joint Learning for Pulmonary Nodule Segmentation, Attributes and Malignancy Prediction—0
Joint Liver and Hepatic Lesion Segmentation in MRI using a Hybrid CNN with Transformer Layers—0
Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan—0
Kernel-based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks—0
KEVS: Enhancing Segmentation of Visceral Adipose Tissue in Pre-Cystectomy CT with Gaussian Kernel Density Estimation—0
Kidney and Kidney Tumor Segmentation using a Logical Ensemble of U-nets with Volumetric Validation—0
Kidney and Kidney Tumour Segmentation in CT Images—0
Knee Osteoarthritis Severity Prediction using an Attentive Multi-Scale Deep Convolutional Neural Network—0
Label-efficient Multi-organ Segmentation Method with Diffusion Model—0
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