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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 701–750 of 1207 papers

TitleStatusHype
Temporal and volumetric denoising via quantile sparse image prior—0
Temporal Scalability of Dynamic Volume Data Using Mesh Compensated Wavelet Lifting—0
Tensor-based formulation and nuclear norm regularization for multi-energy computed tomography—0
Texture-Aware StarGAN for CT data harmonisation—0
Texture Matching GAN for CT Image Enhancement—0
AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons—0
A Rigid Registration Method in TEVAR—0
The establishment of static digital humans and the integration with spinal models—0
The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study—0
Three-dimensional Generative Adversarial Nets for Unsupervised Metal Artifact Reduction—0
TomoGRAF: A Robust and Generalizable Reconstruction Network for Single-View Computed Tomography—0
Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine—0
TomoSLAM: factor graph optimization for rotation angle refinement in microtomography—0
Topic Modeling for Classification of Clinical Reports—0
Topology-Aware Loss for Aorta and Great Vessel Segmentation in Computed Tomography Images—0
Total Variation Regularization for Tomographic Reconstruction of Cylindrically Symmetric Objects—0
Towards Automatic Abdominal MRI Organ Segmentation: Leveraging Synthesized Data Generated From CT Labels—0
Towards Head Computed Tomography Image Reconstruction Standardization with Deep Learning Assisted Automatic Detection—0
Towards Patient-Specific Surgical Planning for Bicuspid Aortic Valve Repair: Fully Automated Segmentation of the Aortic Valve in 4D CT—0
Towards radiologist-level cancer risk assessment in CT lung screening using deep learning—0
Towards Transfer Learning for Large-Scale Image Classification Using Annealing-based Quantum Boltzmann Machines—0
Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT—0
Training of deep cross-modality conversion models with a small dataset, and their application in megavoltage CT to kilovoltage CT conversion—0
Transfer Learning by Cascaded Network to identify and classify lung nodules for cancer detection—0
Transfer learning for multi-center classification of chronic obstructive pulmonary disease—0
Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs—0
Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network—0
Quantifying uncertainty in lung cancer segmentation with foundation models applied to mixed-domain datasets—0
TSUBF-Net: Trans-Spatial UNet-like Network with Bi-direction Fusion for Segmentation of Adenoid Hypertrophy in CT—0
TV-regularized CT Reconstruction and Metal Artifact Reduction Using Inequality Constraints with Preconditioning—0
Two Stage Segmentation of Cervical Tumors using PocketNet—0
Sequential Diffusion-Guided Deep Image Prior For Medical Image Reconstruction—0
Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data—0
UMedNeRF: Uncertainty-aware Single View Volumetric Rendering for Medical Neural Radiance Fields—0
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz—0
Uncertainty-Guided Coarse-to-Fine Tumor Segmentation with Anatomy-Aware Post-Processing—0
Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography—0
UNet-3D with Adaptive TverskyCE Loss for Pancreas Medical Image Segmentation—0
U-Net Based Architecture for an Improved Multiresolution Segmentation in Medical Images—0
U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities—0
Unified Supervised-Unsupervised (SUPER) Learning for X-ray CT Image Reconstruction—0
Unlocking Robust Segmentation Across All Age Groups via Continual Learning—0
Unlocking the Potential of Early Epochs: Uncertainty-aware CT Metal Artifact Reduction—0
Unsupervised Acute Intracranial Hemorrhage Segmentation with Mixture Models—0
Unsupervised Contrastive Learning based Transformer for Lung Nodule Detection—0
Unsupervised CT Metal Artifact Learning using Attention-guided beta-CycleGAN—0
Unsupervised denoising for sparse multi-spectral computed tomography—0
Unsupervised Sparse-view Backprojection via Convolutional and Spatial Transformer Networks—0
UnWave-Net: Unrolled Wavelet Network for Compton Tomography Image Reconstruction—0
User lung cancer classification using efficientnet from ct scan images—0
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