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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
Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT ImagesCode1
Multi-Scale Supervised 3D U-Net for Kidneys and Kidney Tumor SegmentationCode1
COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-raysCode1
COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray ImagesCode1
COVID-CT-Dataset: A CT Scan Dataset about COVID-19Code1
U-Det: A Modified U-Net architecture with bidirectional feature network for lung nodule segmentationCode1
Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography VolumesCode1
Multimodal fusion of imaging and genomics for lung cancer recurrence predictionCode1
An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical ImagesCode1
Deep Transfer Convolutional Neural Network and Extreme Learning Machine for Lung Nodule Diagnosis on CT imagesCode1
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image SegmentationCode1
Tapering Analysis of Airways with BronchiectasisCode1
Disentangled Representation Learning in Cardiac Image AnalysisCode1
MRI to CT Translation with GANsCode1
The Liver Tumor Segmentation Benchmark (LiTS)Code1
Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox DetectorCode1
From Variability To Accuracy: Conditional Bernoulli Diffusion Models with Consensus-Driven Correction for Thin Structure Segmentation—0
Latent Space Consistency for Sparse-View CT Reconstruction—0
Enhancing Synthetic CT from CBCT via Multimodal Fusion and End-To-End RegistrationCode0
μ^2Tokenizer: Differentiable Multi-Scale Multi-Modal Tokenizer for Radiology Report Generation—0
Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration—0
SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided PromptingCode0
Adaptive Multi-resolution Hash-Encoding Framework for INR-based Dental CBCT Reconstruction with Truncated FOV—0
Taming Stable Diffusion for Computed Tomography Blind Super-Resolution—0
Enhancing Synthetic CT from CBCT via Multimodal Fusion: A Study on the Impact of CBCT Quality and Alignment—0
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