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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 76–100 of 1207 papers

TitleStatusHype
Dual Multi-scale Mean Teacher Network for Semi-supervised Infection Segmentation in Chest CT Volume for COVID-19Code1
On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT SettingCode1
Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT ScansCode1
FocalUNETR: A Focal Transformer for Boundary-aware Segmentation of CT ImagesCode1
Deep 3D Vessel Segmentation based on Cross Transformer NetworkCode1
Voxels Intersecting along Orthogonal Levels Attention U-Net for Intracerebral Haemorrhage Segmentation in Head CTCode1
LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule DetectionCode1
Quad-Net: Quad-domain Network for CT Metal Artifact ReductionCode1
Body Composition Assessment with Limited Field-of-view Computed Tomography: A Semantic Image Extension PerspectiveCode1
Domain Knowledge Driven 3D Dose Prediction Using Moment-Based Loss FunctionCode1
Near-Exact Recovery for Tomographic Inverse Problems via Deep LearningCode1
GradICON: Approximate Diffeomorphisms via Gradient Inverse ConsistencyCode1
Dual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CTCode1
Hypernetwork-based Personalized Federated Learning for Multi-Institutional CT ImagingCode1
COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT ImagesCode1
Siamese Encoder-based Spatial-Temporal Mixer for Growth Trend Prediction of Lung Nodules on CT ScansCode1
PatchNR: Learning from Very Few Images by Patch Normalizing Flow RegularizationCode1
Global Contrast Masked Autoencoders Are Powerful Pathological Representation LearnersCode1
Adaptive Convolutional Dictionary Network for CT Metal Artifact ReductionCode1
Unsupervised Multi-Modal Medical Image Registration via Discriminator-Free Image-to-Image TranslationCode1
Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-ResolutionCode1
LiftReg: Limited Angle 2D/3D Deformable RegistrationCode1
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed TomographyCode1
MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-rayCode1
Lymphoma segmentation from 3D PET-CT images using a deep evidential networkCode1
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