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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 151–175 of 1207 papers

TitleStatusHype
Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge—0
CT-AGRG: Automated Abnormality-Guided Report Generation from 3D Chest CT Volumes—0
FQGA-single: Towards Fewer Training Epochs and Fewer Model Parameters for Image-to-Image Translation Tasks—0
Learned denoising with simulated and experimental low-dose CT data—0
Dual-Domain CLIP-Assisted Residual Optimization Perception Model for Metal Artifact Reduction—0
Improved 3D Whole Heart Geometry from Sparse CMR SlicesCode0
Deep Inertia L_p Half-Quadratic Splitting Unrolling Network for Sparse View CT Reconstruction—0
BeyondCT: A deep learning model for predicting pulmonary function from chest CT scans—0
Counterfactuals and Uncertainty-Based Explainable Paradigm for the Automated Detection and Segmentation of Renal Cysts in Computed Tomography Images: A Multi-Center Study—0
Iterative CT Reconstruction via Latent Variable Optimization of Shallow Diffusion Models—0
Segment anything model 2: an application to 2D and 3D medical imagesCode2
X-Recon: Learning-based Patient-specific High-Resolution CT Reconstruction from Orthogonal X-Ray ImagesCode0
Deep Learning CT Image Restoration using System Blur and Noise Models—0
DiffuX2CT: Diffusion Learning to Reconstruct CT Images from Biplanar X-Rays—0
Edge Projection-Based Adaptive View Selection for Cone-Beam CT—0
Leveraging Multimodal CycleGAN for the Generation of Anatomically Accurate Synthetic CT Scans from MRIs—0
Adaptive Compressed Sensing with Diffusion-Based Posterior SamplingCode1
Lung-CADex: Fully automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images—0
A Cross Spatio-Temporal Pathology-based Lung Nodule DatasetCode0
A Lung Nodule Dataset with Histopathology-based Cancer Type AnnotationCode1
DFS-based fast crack detection—0
Total Variation Regularization for Tomographic Reconstruction of Cylindrically Symmetric Objects—0
Pixel-weighted Multi-pose Fusion for Metal Artifact Reduction in X-ray Computed Tomography—0
Deep learning-based brain segmentation model performance validation with clinical radiotherapy CT—0
Lesion-Aware Cross-Phase Attention Network for Renal Tumor Subtype Classification on Multi-Phase CT Scans—0
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