External validation of deep learning algorithms for radiologic diagnosis: a systematic review
Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
Advances in deep learning-based medical image analysis
Importance. With the booming growth of artificial intelligence (AI), especially the recent
advancements of deep learning, utilizing advanced deep learning-based methods for …
advancements of deep learning, utilizing advanced deep learning-based methods for …
Semi-supervised medical image segmentation via cross teaching between cnn and transformer
Recently, deep learning with Convolutional Neural Networks (CNNs) and Transformers has
shown encouraging results in fully supervised medical image segmentation. However, it is …
shown encouraging results in fully supervised medical image segmentation. However, it is …
How artificial intelligence improves radiological interpretation in suspected pulmonary embolism
AB Cheikh, G Gorincour, H Nivet, J May, M Seux… - European …, 2022 - Springer
Objectives To evaluate and compare the diagnostic performances of a commercialized
artificial intelligence (AI) algorithm for diagnosing pulmonary embolism (PE) on CT …
artificial intelligence (AI) algorithm for diagnosing pulmonary embolism (PE) on CT …
Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis
Background Subarachnoid hemorrhage from cerebral aneurysm rupture is a major cause of
morbidity and mortality. Early aneurysm identification, aided by automated systems, may …
morbidity and mortality. Early aneurysm identification, aided by automated systems, may …
A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images
Congenital heart disease (CHD) is the most common type of birth defect. Without timely
detection and treatment, approximately one-third of children with CHD would die in the infant …
detection and treatment, approximately one-third of children with CHD would die in the infant …
[HTML][HTML] Paradigm shift from Artificial Neural Networks (ANNs) to deep Convolutional Neural Networks (DCNNs) in the field of medical image processing
Images and other types of unstructural data in the medical domain are rapidly becoming
data-intensive. Actionable insights from these complex data present new opportunities but …
data-intensive. Actionable insights from these complex data present new opportunities but …
Artificial intelligence with deep learning in nuclear medicine and radiology
The use of deep learning in medical imaging has increased rapidly over the past few years,
finding applications throughout the entire radiology pipeline, from improved scanner …
finding applications throughout the entire radiology pipeline, from improved scanner …
Metallic artifacts-free spectral computed tomography angiography based on renal clearable bismuth chelate
G Shu, L Zhao, F Li, Y Jiang, X Zhang, C Yu, J Pan… - Biomaterials, 2024 - Elsevier
Computed tomography angiography (CTA) is one of the most important diagnosis
techniques for various vascular diseases in clinic. However, metallic artifacts caused by …
techniques for various vascular diseases in clinic. However, metallic artifacts caused by …
EdgeSVDNet: 5G-enabled detection and classification of vision-threatening diabetic retinopathy in retinal fundus images
The rise of vision-threatening diabetic retinopathy (VTDR) underscores the imperative for
advanced and efficient early detection mechanisms. With the integration of the Internet of …
advanced and efficient early detection mechanisms. With the integration of the Internet of …