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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 551–575 of 1207 papers

TitleStatusHype
PhD Thesis. Computer-Aided Assessment of Tuberculosis with Radiological Imaging: From rule-based methods to Deep Learning—0
Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image—0
Lesion classification by model-based feature extraction: A differential affine invariant model of soft tissue elasticity—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
PatchNR: Learning from Very Few Images by Patch Normalizing Flow RegularizationCode1
3D helical CT Reconstruction with a Memory Efficient Learned Primal-Dual Architecture—0
Generation of Artificial CT Images using Patch-based Conditional Generative Adversarial NetworksCode0
Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT's Semantic SegmentationCode0
Combining Deep Learning and Adaptive Sparse Modeling for Low-dose CT Reconstruction—0
Global Contrast Masked Autoencoders Are Powerful Pathological Representation LearnersCode1
Adaptive Convolutional Dictionary Network for CT Metal Artifact ReductionCode1
Nonconvex L_ 1/2 -Regularized Nonlocal Self-similarity Denoiser for Compressive Sensing based CT Reconstruction—0
On Scale Space Radon Transform, Properties and Application in CT Image Reconstruction—0
Using Deep Learning-based Features Extracted from CT scans to Predict Outcomes in COVID-19 Patients—0
HRCTCov19 -- A High-Resolution Chest CT Scan Image Dataset for COVID-19 Diagnosis and Differentiation—0
Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference—0
The Batch Artifact Scanning Protocol: A new method using computed tomography (CT) to rapidly create three-dimensional models of objects from large collections en masseCode0
Unsupervised Contrastive Learning based Transformer for Lung Nodule Detection—0
Unsupervised Multi-Modal Medical Image Registration via Discriminator-Free Image-to-Image TranslationCode1
Fast and Robust Femur Segmentation from Computed Tomography Images for Patient-Specific Hip Fracture Risk Screening—0
Multi-organ Segmentation Network with Adversarial Performance Validator—0
Interpretable Vertebral Fracture Quantification via Anchor-Free Landmarks LocalizationCode0
How to Register a Live onto a Liver ? Partial Matching in the Space of VarifoldsCode0
A Post-Processing Tool and Feasibility Study for Three-Dimensional Imaging with Electrical Impedance Tomography During Deep Brain Stimulation SurgeryCode0
Ischemic Stroke Lesion Segmentation Using Adversarial Learning—0
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