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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 301–350 of 1207 papers

TitleStatusHype
MD-IQA: Learning Multi-scale Distributed Image Quality Assessment with Semi Supervised Learning for Low Dose CTCode0
Cross-dataset domain adaptation for the classification COVID-19 using chest computed tomography images—0
UMedNeRF: Uncertainty-aware Single View Volumetric Rendering for Medical Neural Radiance Fields—0
Single-shot Tomography of Discrete Dynamic ObjectsCode0
Interpretable Geoscience Artificial Intelligence (XGeoS-AI): Application to Demystify Image Recognition—0
INeAT: Iterative Neural Adaptive Tomography—0
Low-Dose CT Image Enhancement Using Deep Learning—0
Enhanced Synthetic MRI Generation from CT Scans Using CycleGAN with Feature Extraction—0
Parameter-Efficient Methods for Metastases Detection from Clinical Notes—0
AutoCT: Automated CT registration, segmentation, and quantification—0
Graph-based multimodal multi-lesion DLBCL treatment response prediction from PET images—0
Bayesian imaging inverse problem with SA-Roundtrip prior via HMC-pCN samplerCode0
Deep Learning Models for Classification of COVID-19 Cases by Medical Images—0
Synthetic Data as Validation—0
AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons—0
Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical DiagnosisCode1
Vision Transformers increase efficiency of 3D cardiac CT multi-label segmentationCode0
Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT—0
High Accuracy and Cost-Saving Active Learning 3D WD-UNet for Airway Segmentation—0
Latent Diffusion Model for Medical Image Standardization and Enhancement—0
AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical KnowledgeCode0
Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction—0
Swin-Tempo: Temporal-Aware Lung Nodule Detection in CT Scans as Video Sequences Using Swin Transformer-Enhanced UNet—0
Graph data modelling for outcome prediction in oropharyngeal cancer patients—0
Synthetic CT Generation via Variant Invertible Network for All-digital Brain PET Attenuation CorrectionCode0
Predicting Lung Cancer's Metastats' Locations Using Bioclinical Model—0
Self-distilled Masked Attention guided masked image modeling with noise Regularized Teacher (SMART) for medical image analysis—0
Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT—0
Abdominal multi-organ segmentation in CT using Swinunter—0
Attention and Pooling based Sigmoid Colon Segmentation in 3D CT images—0
Autopet Challenge 2023: nnUNet-based whole-body 3D PET-CT Tumour SegmentationCode0
Solving Low-Dose CT Reconstruction via GAN with Local Coherence—0
Design of Novel Loss Functions for Deep Learning in X-ray CT—0
Inter-vendor harmonization of Computed Tomography (CT) reconstruction kernels using unpaired image translation—0
Interpretable 3D Multi-Modal Residual Convolutional Neural Network for Mild Traumatic Brain Injury Diagnosis—0
Auto-Lesion Segmentation with a Novel Intensity Dark Channel Prior for COVID-19 Detection—0
AutoPET Challenge 2023: Sliding Window-based Optimization of U-NetCode1
Scribble-based 3D Multiple Abdominal Organ Segmentation via Triple-branch Multi-dilated Network with Pixel- and Class-wise Consistency—0
Deep conditional generative models for longitudinal single-slice abdominal computed tomography harmonizationCode0
M3Dsynth: A dataset of medical 3D images with AI-generated local manipulationsCode0
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic DataCode0
A Localization-to-Segmentation Framework for Automatic Tumor Segmentation in Whole-Body PET/CT ImagesCode0
SdCT-GAN: Reconstructing CT from Biplanar X-Rays with Self-driven Generative Adversarial NetworksCode1
An Empirical Analysis for Zero-Shot Multi-Label Classification on COVID-19 CT Scans and Uncurated Reports—0
User lung cancer classification using efficientnet from ct scan images—0
Multi-stage Deep Learning Artifact Reduction for Pallel-beam Computed Tomography—0
Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual DomainsCode1
Attention-based CT Scan Interpolation for Lesion Segmentation of Colorectal Liver Metastases—0
High-risk Factor Prediction in Lung Cancer Using Thin CT Scans: An Attention-Enhanced Graph Convolutional Network Approach—0
PECon: Contrastive Pretraining to Enhance Feature Alignment between CT and EHR Data for Improved Pulmonary Embolism DiagnosisCode0
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