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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 1051–1075 of 1207 papers

TitleStatusHype
Dense Depth Estimation in Monocular Endoscopy with Self-supervised Learning MethodsCode0
Multi-Depth Fusion Network for Whole-Heart CT Image Segmentation—0
Sinogram interpolation for sparse-view micro-CT with deep learning neural network—0
SAPSAM - Sparsely Annotated Pathological Sign Activation Maps - A novel approach to train Convolutional Neural Networks on lung CT scans using binary labels only—0
Labelling Vertebrae with 2D Reformations of Multidetector CT Images: An Adversarial Approach for Incorporating Prior Knowledge of Spine Anatomy—0
Robust X-ray Sparse-view Phase Tomography via Hierarchical Synthesis Convolutional Neural Networks—0
ACNN: a Full Resolution DCNN for Medical Image SegmentationCode0
Automated Segmentation of CT Scans for Normal Pressure HydrocephalusCode0
ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example MiningCode0
MRI to CT Translation with GANsCode1
SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells—0
The Liver Tumor Segmentation Benchmark (LiTS)Code1
Reference Setup for Quantitative Comparison of Segmentation Techniques for Short Glass Fiber CT Data—0
Gated-Dilated Networks for Lung Nodule Classification in CT scans—0
Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images—0
Montage based 3D Medical Image Retrieval from Traumatic Brain Injury Cohort using Deep Convolutional Neural Network—0
Practical Window Setting Optimization for Medical Image Deep LearningCode0
Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image Reconstruction—0
Deep learning based automatic segmentation of lumbosacral nerves on non-contrast CT for radiographic evaluation: a pilot study—0
Low-Dose CT via Deep CNN with Skip Connection and Network in Network—0
False Positive Reduction in Lung Computed Tomography Images using Convolutional Neural NetworksCode0
Finding and Following of Honeycombing Regions in Computed Tomography Lung Images by Deep Learning—0
Block Matching Frame based Material Reconstruction for Spectral CT—0
TV-regularized CT Reconstruction and Metal Artifact Reduction Using Inequality Constraints with Preconditioning—0
Computationally Efficient Deep Neural Network for Computed Tomography Image Reconstruction—0
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