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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 1151–1175 of 1207 papers

TitleStatusHype
Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules—0
Topic Modeling for Classification of Clinical Reports—0
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks—0
Automatic Localization of Deep Stimulation Electrodes Using Trajectory-based Segmentation Approach—0
Early Experiences with Crowdsourcing Airway Annotations in Chest CT—0
Volume Calculation of CT lung Lesions based on Halton Low-discrepancy Sequences—0
Compression Fractures Detection on CT—0
A Cascaded Convolutional Neural Network for X-ray Low-dose CT Image Denoising—0
PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image ReconstructionCode0
A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes—0
Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction—0
Deep Learning with Domain Adaptation for Accelerated Projection-Reconstruction MRCode0
Multi-scale Image Fusion Between Pre-operative Clinical CT and X-ray Microtomography of Lung Pathology—0
Robust and fully automated segmentation of mandible from CT scans—0
Spatial Aggregation of Holistically-Nested Convolutional Neural Networks for Automated Pancreas Localization and Segmentation—0
Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling—0
Transfer learning for multi-center classification of chronic obstructive pulmonary disease—0
Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction—0
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge—0
Medical Image Synthesis with Context-Aware Generative Adversarial Networks—0
Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study—0
Computer Aided Detection of Oral Lesions on CT ImagesCode0
Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis—0
Validation of Tsallis Entropy In Inter-Modality Neuroimage Registration—0
Reliability of PET/CT shape and heterogeneity features in functional and morphological components of Non-Small Cell Lung Cancer tumors: a repeatability analysis in a prospective multi-center cohort—0
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