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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 626–650 of 1207 papers

TitleStatusHype
Robust Cochlear Modiolar Axis Detection in CT—0
Robust deep labeling of radiological emphysema subtypes using squeeze and excitation convolutional neural networks: The MESA Lung and SPIROMICS Studies—0
Robustness Investigation on Deep Learning CT Reconstruction for Real-Time Dose Optimization—0
Robust Quantification of Percent Emphysema on CT via Domain Attention: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study—0
Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Images—0
Robust X-ray Sparse-view Phase Tomography via Hierarchical Synthesis Convolutional Neural Networks—0
S3TU-Net: Structured Convolution and Superpixel Transformer for Lung Nodule Segmentation—0
SAPSAM - Sparsely Annotated Pathological Sign Activation Maps - A novel approach to train Convolutional Neural Networks on lung CT scans using binary labels only—0
Scatter Correction in X-ray CT by Physics-Inspired Deep Learning—0
Scopeformer: n-CNN-ViT Hybrid Model for Intracranial Hemorrhage Classification—0
Screening COVID-19 Based on CT/CXR Images & Building a Publicly Available CT-scan Dataset of COVID-19—0
Scribble-based 3D Multiple Abdominal Organ Segmentation via Triple-branch Multi-dilated Network with Pixel- and Class-wise Consistency—0
SCULPTOR: Skeleton-Consistent Face Creation Using a Learned Parametric Generator—0
SECP-Net: SE-Connection Pyramid Network of Organ At Risk Segmentation for Nasopharyngeal Carcinoma—0
SegBook: A Simple Baseline and Cookbook for Volumetric Medical Image Segmentation—0
Segmentation Criteria in the Problem of Porosity Determination based on CT Scans—0
Segmentation of Aortic Vessel Tree in CT Scans with Deep Fully Convolutional Networks—0
Self-Attention Generative Adversarial Network for Iterative Reconstruction of CT Images—0
Self-distilled Masked Attention guided masked image modeling with noise Regularized Teacher (SMART) for medical image analysis—0
Self is the Best Learner: CT-free Ultra-Low-Dose PET Organ Segmentation via Collaborating Denoising and Segmentation Learning—0
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis—0
Self-Supervised Denoiser Framework—0
Self-Supervised Learning for Biological Sample Localization in 3D Tomographic Images—0
Self-Supervised Learning for Segmentation—0
Self-supervised Learning from 100 Million Medical Images—0
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