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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 851–875 of 1207 papers

TitleStatusHype
3D helical CT Reconstruction with a Memory Efficient Learned Primal-Dual Architecture—0
3D-Morphomics, Morphological Features on CT scans for lung nodule malignancy diagnosis—0
3D Organ Shape Reconstruction from Topogram Images—0
3D Tomographic Pattern Synthesis for Enhancing the Quantification of COVID-19—0
3D U-Net for segmentation of COVID-19 associated pulmonary infiltrates using transfer learning: State-of-the-art results on affordable hardware—0
4D VQ-GAN: Synthesising Medical Scans at Any Time Point for Personalised Disease Progression Modelling of Idiopathic Pulmonary Fibrosis—0
A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT—0
Abdominal multi-organ segmentation in CT using Swinunter—0
A Bottom-Up Approach for Automatic Pancreas Segmentation in Abdominal CT Scans—0
A Cascaded Convolutional Neural Network for X-ray Low-dose CT Image Denoising—0
Accelerated Optimization of Implicit Neural Representations for CT Reconstruction—0
Accurate Lung Nodules Segmentation with Detailed Representation Transfer and Soft Mask Supervision—0
Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning—0
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks—0
Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST—0
AC-IND: Sparse CT reconstruction based on attenuation coefficient estimation and implicit neural distribution—0
A combined Machine Learning and Finite Element Modelling tool for the surgical planning of craniosynostosis correction—0
A computationally efficient reconstruction algorithm for circular cone-beam computed tomography using shallow neural networks—0
A Computer-Aided Diagnosis System Using Artificial Intelligence for Hip Fractures -Multi-Institutional Joint Development Research-—0
A Continual Learning-driven Model for Accurate and Generalizable Segmentation of Clinically Comprehensive and Fine-grained Whole-body Anatomies in CT—0
A convergence proof of the split Bregman method for regularized least-squares problems—0
A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning—0
Active CT Reconstruction with a Learned Sampling Policy—0
Active Learning on Medical Image—0
Adaptation to CT Reconstruction Kernels by Enforcing Cross-domain Feature Maps Consistency—0
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