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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 451–500 of 1207 papers

TitleStatusHype
Direct high-order edge-preserving regularization for tomographic image reconstruction—0
Disassemblable Fieldwork CT Scanner Using a 3D-printed Calibration Phantom—0
Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules—0
Display Field-Of-View Agnostic Robust CT Kernel Synthesis Using Model-Based Deep Learning—0
Distant Domain Transfer Learning for Medical Imaging—0
Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury—0
Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction—0
Divide to Conquer: A Field Decomposition Approach for Multi-Organ Whole-Body CT Image Registration—0
DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection—0
DLIMD: Dictionary Learning based Image-domain Material Decomposition for spectral CT—0
CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans—0
Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT Image Segmentation—0
A GLCM Embedded CNN Strategy for Computer-aided Diagnosis in Intracerebral Hemorrhage—0
Domain Adaptation of Automated Treatment Planning from Computed Tomography to Magnetic Resonance—0
Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image—0
CovidExpert: A Triplet Siamese Neural Network framework for the detection of COVID-19—0
COVID CT-Net: Predicting Covid-19 From Chest CT Images Using Attentional Convolutional Network—0
Attention-based CT Scan Interpolation for Lesion Segmentation of Colorectal Liver Metastases—0
A combined Machine Learning and Finite Element Modelling tool for the surgical planning of craniosynostosis correction—0
DPER: Diffusion Prior Driven Neural Representation for Limited Angle and Sparse View CT Reconstruction—0
Dual-branch residual network for lung nodule segmentation—0
Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms—0
COVID-CLNet: COVID-19 Detection with Compressive Deep Learning Approaches—0
Dual-Domain CLIP-Assisted Residual Optimization Perception Model for Metal Artifact Reduction—0
Attention and Pooling based Sigmoid Colon Segmentation in 3D CT images—0
Aging prediction using deep generative model toward the development of preventive medicine—0
Dual Network Architecture for Few-view CT -- Trained on ImageNet Data and Transferred for Medical Imaging—0
Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia—0
Dual Windows Are Significant: Learning from Mediastinal Window and Focusing on Lung Window—0
DuDoNet: Dual Domain Network for CT Metal Artifact Reduction—0
Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography—0
CHS-Net: A Deep learning approach for hierarchical segmentation of COVID-19 infected CT images—0
DuoLift-GAN:Reconstructing CT from Single-view and Biplanar X-Rays with Generative Adversarial Networks—0
Dynamic Angle Selection in X-Ray CT: A Reinforcement Learning Approach to Optimal Stopping—0
Evaluation of Scan-Line Optimization for 3D Medical Image Registration—0
Early Experiences with Crowdsourcing Airway Annotations in Chest CT—0
AttentionAnatomy: A unified framework for whole-body organs at risk segmentation using multiple partially annotated datasets—0
Evaluating the Posterior Sampling Ability of Plug&Play Diffusion Methods in Sparse-View CT—0
Effect of Input Size on the Classification of Lung Nodules Using Convolutional Neural Networks—0
ClamNet: Using contrastive learning with variable depth Unets for medical image segmentation—0
Efficient liver segmentation with 3D CNN using computed tomography scans—0
Efficient Low Dose X-ray CT Reconstruction through Sparsity-Based MAP Modeling—0
Classical and learned MR to pseudo-CT mappings for accurate transcranial ultrasound simulation—0
Efficient Pretraining Model based on Multi-Scale Local Visual Field Feature Reconstruction for PCB CT Image Element Segmentation—0
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios—0
Atrous Residual Interconnected Encoder to Attention Decoder Framework for Vertebrae Segmentation via 3D Volumetric CT Images—0
Employing Weak Annotations for Medical Image Analysis Problems—0
Empowering Medical Imaging with Artificial Intelligence: A Review of Machine Learning Approaches for the Detection, and Segmentation of COVID-19 Using Radiographic and Tomographic Images—0
End2end-ALARA: Approaching the ALARA Law in CT Imaging with End-to-end Learning—0
Age-Conditioned Synthesis of Pediatric Computed Tomography with Auxiliary Classifier Generative Adversarial Networks—0
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