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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 1101–1150 of 1207 papers

TitleStatusHype
Asymmetric 3D Context Fusion for Universal Lesion DetectionCode0
Spatiotemporal tomography based on scattered multiangular signals and its application for resolving evolving clouds using moving platformsCode0
View it like a radiologist: Shifted windows for deep learning augmentation of CT imagesCode0
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19Code0
MVMS-RCN: A Dual-Domain Unfolding CT Reconstruction with Multi-sparse-view and Multi-scale Refinement-correctionCode0
MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion DetectionCode0
Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisy-or NetworkCode0
Data-Efficient Limited-Angle CT Using Deep Priors and RegularizationCode0
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT SlicesCode0
Enhancing Synthetic CT from CBCT via Multimodal Fusion and End-To-End RegistrationCode0
SR4ZCT: Self-supervised Through-plane Resolution Enhancement for CT Images with Arbitrary Resolution and OverlapCode0
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse ProblemsCode0
Label Refinement Network from Synthetic Error Augmentation for Medical Image SegmentationCode0
RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT ScansCode0
Enhancing COVID-19 Severity Analysis through Ensemble MethodsCode0
Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier SeriesCode0
AIforCOVID: predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre studyCode0
Artifact Disentanglement Network for Unsupervised Metal Artifact ReductionCode0
End-to-end reconstruction meets data-driven regularization for inverse problemsCode0
Towards Fair Medical AI: Adversarial Debiasing of 3D CT Foundation EmbeddingsCode0
A Post-Processing Tool and Feasibility Study for Three-Dimensional Imaging with Electrical Impedance Tomography During Deep Brain Stimulation SurgeryCode0
STAN-CT: Standardizing CT Image using Generative Adversarial NetworkCode0
Learning Difference-of-Convex Regularizers for Inverse Problems: A Flexible Framework with Theoretical GuaranteesCode0
SmoothSegNet: A Global-Local Framework for Liver Tumor Segmentation with Clinical KnowledgeInformed Label SmoothingCode0
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty AlignmentCode0
AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical KnowledgeCode0
COVID-FACT: A Fully-Automated Capsule Network-based Framework for Identification of COVID-19 Cases from Chest CT scansCode0
Learning to Distill Global Representation for Sparse-View CTCode0
X2CT-GAN: Reconstructing CT from Biplanar X-Rays with Generative Adversarial NetworksCode0
LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CTCode0
Towards synthetic generation of realistic wooden logsCode0
Data-Driven Computational Imaging for Scientific DiscoveryCode0
A Cone-Beam X-Ray CT Data Collection designed for Machine LearningCode0
Towards Universal Text-driven CT Image SegmentationCode0
3D Solid Spherical Bispectrum CNNs for Biomedical Texture AnalysisCode0
Virtual imaging trials improved the transparency and reliability of AI systems in COVID-19 imagingCode0
Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT ClassificationCode0
Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT's Semantic SegmentationCode0
COVID-19 Lung Lesion Segmentation Using a Sparsely Supervised Mask R-CNN on Chest X-rays Automatically Computed from Volumetric CTsCode0
SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided PromptingCode0
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic DataCode0
Efficient 3D Fully Convolutional Networks for Pulmonary Lobe Segmentation in CT ImagesCode0
DuDoTrans: Dual-Domain Transformer Provides More Attention for Sinogram Restoration in Sparse-View CT ReconstructionCode0
Structure Regularized Attentive Network for Automatic Femoral Head Necrosis Diagnosis and LocalizationCode0
A Closer Look at Spatial-Slice Features Learning for COVID-19 DetectionCode0
Web Diagnosis for COVID-19 and Pneumonia Based on Computed Tomography Scans and X-raysCode0
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact ReductionCode0
DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT ImagesCode0
Super-Resolution Based Patch-Free 3D Image Segmentation with High-Frequency GuidanceCode0
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric UncertaintyCode0
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