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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 1076–1100 of 1207 papers

TitleStatusHype
Cylindrical Transform: 3D Semantic Segmentation of Kidneys With Limited Annotated Images—0
Modern Convex Optimization to Medical Image Analysis—0
Crowdsourcing Lung Nodules Detection and Annotation—0
3D Path Planning from a Single 2D Fluoroscopic Image for Robot Assisted Fenestrated Endovascular Aortic RepairCode0
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapyCode0
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection—0
Super-Resolution and Sparse View CT Reconstruction—0
Automatic Lung Cancer Prediction from Chest X-ray Images Using Deep Learning Approach—0
A method for automatic forensic facial reconstruction based on dense statistics of soft tissue thickness—0
Deep Boosted Regression for MR to CT Synthesis—0
Holographic Visualisation of Radiology Data and Automated Machine Learning-based Medical Image Segmentation—0
Automatic Airway Segmentation in chest CT using Convolutional Neural Networks—0
CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)—0
Metal Artifact Reduction in Cone-Beam X-Ray CT via Ray Profile Correction—0
Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation—0
Non-local Low-rank Cube-based Tensor Factorization for Spectral CT Reconstruction—0
Clearing noisy annotations for computed tomography imagingCode0
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement—0
Computed Tomography Image Enhancement using 3D Convolutional Neural Network—0
Stroke lesion detection using convolutional neural networks—0
Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST—0
Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox DetectorCode1
Classification of lung nodules in CT images based on Wasserstein distance in differential geometry—0
3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion DetectionCode0
CT-image Super Resolution Using 3D Convolutional Neural Network—0
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