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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 1001–1050 of 1207 papers

TitleStatusHype
Kidney and Kidney Tumor Segmentation using a Logical Ensemble of U-nets with Volumetric Validation—0
SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis—0
Multi-Contrast Super-Resolution MRI Through a Progressive Network—0
Automatic segmentation of kidney and liver tumors in CT images—0
BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization—0
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact ReductionCode0
Multi-Scale Learned Iterative ReconstructionCode0
NLP Automation to Read Radiological Reports to Detect the Stage of Cancer Among Lung Cancer Patients—0
Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities—0
Delving Deep into Liver Focal Lesion Detection: A Preliminary Study—0
Domain specific cues improve robustness of deep learning based segmentation of ct volumes—0
Improving Deep Lesion Detection Using 3D Contextual and Spatial AttentionCode0
Robust Cochlear Modiolar Axis Detection in CT—0
Dual Network Architecture for Few-view CT -- Trained on ImageNet Data and Transferred for Medical Imaging—0
DuDoNet: Dual Domain Network for CT Metal Artifact Reduction—0
Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction—0
Automated Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction—0
Fully Automatic Liver Attenuation Estimation Combing CNN Segmentation and Morphological OperationsCode0
Automatic Intracranial Brain Segmentation from Computed Tomography Head Images—0
Differentiable probabilistic models of scientific imaging with the Fourier slice theoremCode0
DC2Anet: Generating Lumbar Spine MR Images from CT Scan Data Based on Semi-Supervised LearningCode0
Deep Variational Networks with Exponential Weighting for Learning Computed Tomography—0
Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks—0
A GLCM Embedded CNN Strategy for Computer-aided Diagnosis in Intracerebral Hemorrhage—0
Artifact Disentanglement Network for Unsupervised Metal Artifact ReductionCode0
Lung cancer screening with low-dose CT scans using a deep learning approach—0
PHT-bot: Deep-Learning based system for automatic risk stratification of COPD patients based upon signs of Pulmonary Hypertension—0
Dual-branch residual network for lung nodule segmentation—0
A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT—0
X2CT-GAN: Reconstructing CT from Biplanar X-Rays with Generative Adversarial NetworksCode0
A Cone-Beam X-Ray CT Data Collection designed for Machine LearningCode0
Two-Stage Convolutional Neural Network Architecture for Lung Nodule Detection—0
DLIMD: Dictionary Learning based Image-domain Material Decomposition for spectral CT—0
Lung Nodule Classification using Deep Local-Global NetworksCode0
Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection—0
Fast Enhanced CT Metal Artifact Reduction using Data Domain Deep LearningCode0
Deep Learning Based Computed Tomography Whys and Wherefores—0
DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule DetectionCode0
Controlling Neural Networks via Energy Dissipation—0
Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning—0
The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical OutcomesCode0
Combining many-objective radiomics and 3D convolutional neural network through evidential reasoning to predict lymph node metastasis in head and neck cancer—0
3D Organ Shape Reconstruction from Topogram Images—0
An Approach for Adaptive Automatic Threat Recognition Within 3D Computed Tomography Images for Baggage Security Screening—0
Automatic Pulmonary Lobe Segmentation Using Deep LearningCode0
Automated pulmonary nodule detection using 3D deep convolutional neural networks—0
An End-to-end Framework For Integrated Pulmonary Nodule Detection and False Positive Reduction—0
Convolutional Sparse Coding for Compressed Sensing CT Reconstruction—0
Interactive segmentation of medical images through fully convolutional neural networks—0
Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury—0
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