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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
Benchmarking learned algorithms for computed tomography image reconstruction tasks—0
Benign-Malignant Lung Nodule Classification with Geometric and Appearance Histogram Features—0
Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation Learning—0
BeyondCT: A deep learning model for predicting pulmonary function from chest CT scans—0
Bidirectional Brain Image Translation using Transfer Learning from Generic Pre-trained Models—0
Bi-level Guided Diffusion Models for Zero-Shot Medical Imaging Inverse Problems—0
Bio-Inspired Feature Selection in Brain Disease Detection via an Improved Sparrow Search Algorithm—0
Block Matching Frame based Material Reconstruction for Spectral CT—0
Boosting Deep Transfer Learning for COVID-19 Classification—0
Brain Signals Analysis Based Deep Learning Methods: Recent advances in the study of non-invasive brain signals—0
Breast Cancer Induced Bone Osteolysis Prediction Using Temporal Variational Auto-Encoders—0
Bridged Semantic Alignment for Zero-shot 3D Medical Image Diagnosis—0
Bronchoscopic video synchronization for interactive multimodal inspection of bronchial lesions—0
Cadmium Zinc Telluride (CZT) photon counting detector Characterisation for soft tissue imaging—0
CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans—0
CAFCT-Net: A CNN-Transformer Hybrid Network with Contextual and Attentional Feature Fusion for Liver Tumor Segmentation—0
Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image—0
Capsules for Biomedical Image Segmentation—0
Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks—0
Cardiac Segmentation on CT Images through Shape-Aware Contour Attentions—0
CCTCOVID: COVID-19 Detection from Chest X-Ray Images Using Compact Convolutional Transformers—0
Charting the Path Forward: CT Image Quality Assessment -- An In-Depth Review—0
CHS-Net: A Deep learning approach for hierarchical segmentation of COVID-19 infected CT images—0
CIDI-Lung-Seg: A Single-Click Annotation Tool for Automatic Delineation of Lungs from CT Scans—0
Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network—0
ClamNet: Using contrastive learning with variable depth Unets for medical image segmentation—0
Class-Discriminative Attention Maps for Vision Transformers—0
Classical and learned MR to pseudo-CT mappings for accurate transcranial ultrasound simulation—0
Classification of COVID-19 in Chest CT Images using Convolutional Support Vector Machines—0
Classification of COVID-19 via Homology of CT-SCAN—0
Classification of COVID-19 X-ray Images Using a Combination of Deep and Handcrafted Features—0
Classification of lung cancer subtypes on CT images with synthetic pathological priors—0
Classification of lung nodules in CT images based on Wasserstein distance in differential geometry—0
Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations—0
Closed-Form Approximation of the Total Variation Proximal Operator—0
CNN-Based Projected Gradient Descent for Consistent Image Reconstruction—0
Coarse-to-fine Airway Segmentation Using Multi information Fusion Network and CNN-based Region Growing—0
CodEx: A Modular Framework for Joint Temporal De-blurring and Tomographic Reconstruction—0
Co-Heterogeneous and Adaptive Segmentation from Multi-Source and Multi-Phase CT Imaging Data: A Study on Pathological Liver and Lesion Segmentation—0
Combining Deep Learning and Adaptive Sparse Modeling for Low-dose CT Reconstruction—0
Combining many-objective radiomics and 3D convolutional neural network through evidential reasoning to predict lymph node metastasis in head and neck cancer—0
Combining multimodal information for Metal Artefact Reduction: An unsupervised deep learning framework—0
Comparative Evaluation of 3D and 2D Deep Learning Techniques for Semantic Segmentation in CT Scans—0
Comparing One-step and Two-step Scatter Correction and Density Reconstruction in X-ray CT—0
Compression Fractures Detection on CT—0
Computationally Efficient Deep Neural Network for Computed Tomography Image Reconstruction—0
Computational Scatter Correction for High-Resolution Flat-Panel CT Based on a Fast Monte Carlo Photon Transport Model—0
Computed Tomography Image Enhancement using 3D Convolutional Neural Network—0
Computed Tomography Reconstruction using Generative Energy-Based Priors—0
Concurrent ischemic lesion age estimation and segmentation of CT brain using a Transformer-based network—0
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