[HTML][HTML] Image-based generative artificial intelligence in radiology: comprehensive updates
Generative artificial intelligence (AI) has been applied to images for image quality
enhancement, domain transfer, and augmentation of training data for AI modeling in various …
enhancement, domain transfer, and augmentation of training data for AI modeling in various …
Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology
Artificial intelligence (AI) has numerous applications in radiology. Clinical research studies
to evaluate the AI models are also diverse. Consequently, diverse outcome metrics and …
to evaluate the AI models are also diverse. Consequently, diverse outcome metrics and …
[HTML][HTML] Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes
H Jhang, SJ Park, AR Sul, HY Jang… - Korean Journal of …, 2024 - ncbi.nlm.nih.gov
Objective This study aims to explore the opinions on the insurance coverage of artificial
intelligence (AI), as categorized based on the distinct value elements offered by AI, with a …
intelligence (AI), as categorized based on the distinct value elements offered by AI, with a …
CT Quantification of Interstitial Lung Abnormality and Interstitial Lung Disease: From Technical Challenges to Future Directions
Interstitial lung disease (ILD) encompasses a variety of lung disorders with varying degrees
of inflammation or fibrosis, requiring a combination of clinical, imaging, and pathologic data …
of inflammation or fibrosis, requiring a combination of clinical, imaging, and pathologic data …
Improving functional correlation of quantification of interstitial lung disease by reducing the vendor difference of CT using generative adversarial network (GAN) style …
Objective To assess whether CT style conversion between different CT vendors using a
routable generative adversarial network (RouteGAN) could minimize variation in ILD …
routable generative adversarial network (RouteGAN) could minimize variation in ILD …
Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation …
YC An, JH Kim, JM Noh, KM Yang, YJ Oh… - Thoracic …, 2023 - Wiley Online Library
Background We sought to quantify diffuse parenchymal lung disease (DPLD) extent using
quantitative computed tomography (CT) analysis and to investigate its association with …
quantitative computed tomography (CT) analysis and to investigate its association with …
Conversion of single-energy CT to parametric maps of dual-energy CT using convolutional neural network
Objectives We propose a deep learning (DL) multitask learning framework using
convolutional neural network for a direct conversion of single-energy CT (SECT) to 3 …
convolutional neural network for a direct conversion of single-energy CT (SECT) to 3 …
Correlation between CT-based phenotypes and serum biomarker in interstitial lung diseases
B Shin, YJ Oh, J Kim, SG Park, KS Lee… - BMC Pulmonary Medicine, 2024 - Springer
Background The quantitative analysis of computed tomography (CT) and Krebs von den
Lungen-6 (KL-6) serum level has gained importance in the diagnosis, monitoring, and …
Lungen-6 (KL-6) serum level has gained importance in the diagnosis, monitoring, and …
[HTML][HTML] Uncover This Tech Term: Generative Adversarial Networks
HS Ahmed - Korean Journal of Radiology, 2024 - ncbi.nlm.nih.gov
GANs have several applications in radiology. One major challenge in medical imaging is the
scarcity of large datasets for training AI algorithms. GANs can be advantageous in …
scarcity of large datasets for training AI algorithms. GANs can be advantageous in …
Conversion of single-energy computed tomography to parametric maps of dual-energy computed tomography using convolutional neural network
Objectives: We propose a deep learning (DL) multi-task learning framework using
convolutional neural network (CNN) for a direct conversion of single-energy CT (SECT) to …
convolutional neural network (CNN) for a direct conversion of single-energy CT (SECT) to …