New international guidelines and consensus on the use of lung ultrasound
Following the innovations and new discoveries of the last 10 years in the field of lung
ultrasound (LUS), a multidisciplinary panel of international LUS experts from six countries …
ultrasound (LUS), a multidisciplinary panel of international LUS experts from six countries …
Machine learning for brain stroke: a review
Abstract Machine Learning (ML) delivers an accurate and quick prediction outcome and it
has become a powerful tool in health settings, offering personalized clinical care for stroke …
has become a powerful tool in health settings, offering personalized clinical care for stroke …
Convolutional neural networks for medical image analysis: Full training or fine tuning?
N Tajbakhsh, JY Shin, SR Gurudu… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Training a deep convolutional neural network (CNN) from scratch is difficult because it
requires a large amount of labeled training data and a great deal of expertise to ensure …
requires a large amount of labeled training data and a great deal of expertise to ensure …
Machine learning for medical ultrasound: status, methods, and future opportunities
Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic
imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and …
imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and …
Stacked deep polynomial network based representation learning for tumor classification with small ultrasound image dataset
Ultrasound imaging has been widely used for tumor detection and diagnosis. In ultrasound
based computer-aided diagnosis, feature representation is a crucial step. In recent years …
based computer-aided diagnosis, feature representation is a crucial step. In recent years …
NAG-Net: Nested attention-guided learning for segmentation of carotid lumen-intima interface and media-adventitia interface
Q Huang, L Zhao, G Ren, X Wang, C Liu… - Computers in Biology and …, 2023 - Elsevier
Cardiovascular diseases (CVD), as the leading cause of death in the world, poses a serious
threat to human health. The segmentation of carotid Lumen-intima interface (LII) and Media …
threat to human health. The segmentation of carotid Lumen-intima interface (LII) and Media …
Attention-based UNet deep learning model for plaque segmentation in carotid ultrasound for stroke risk stratification: an artificial intelligence paradigm
Stroke and cardiovascular diseases (CVD) significantly affect the world population. The
early detection of such events may prevent the burden of death and costly surgery …
early detection of such events may prevent the burden of death and costly surgery …
A review on joint carotid intima-media thickness and plaque area measurement in ultrasound for cardiovascular/stroke risk monitoring: artificial intelligence framework
Cardiovascular diseases (CVDs) are the top ten leading causes of death worldwide.
Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial …
Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial …
Deep learning‐based carotid media‐adventitia and lumen‐intima boundary segmentation from three‐dimensional ultrasound images
Purpose Quantification of carotid plaques has been shown to be important for assessing as
well as monitoring the progression and regression of carotid atherosclerosis. Various …
well as monitoring the progression and regression of carotid atherosclerosis. Various …
Two-stage artificial intelligence model for jointly measurement of atherosclerotic wall thickness and plaque burden in carotid ultrasound: A screening tool for …
Motivation The early screening of cardiovascular diseases (CVD) can lead to effective
treatment. Thus, accurate and reliable atherosclerotic carotid wall detection and plaque …
treatment. Thus, accurate and reliable atherosclerotic carotid wall detection and plaque …