[HTML][HTML] Deep learning in medical ultrasound analysis: a review
Ultrasound (US) has become one of the most commonly performed imaging modalities in
clinical practice. It is a rapidly evolving technology with certain advantages and with unique …
clinical practice. It is a rapidly evolving technology with certain advantages and with unique …
Convolutional neural networks for radiologic images: a radiologist's guide
S Soffer, A Ben-Cohen, O Shimon, MM Amitai… - Radiology, 2019 - pubs.rsna.org
Deep learning has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …
recently gained particular attention in the radiology community. This article provides an …
Imaging biomarkers of vulnerable carotid plaques for stroke risk prediction and their potential clinical implications
Stroke represents a massive public health problem. Carotid atherosclerosis plays a
fundamental part in the occurence of ischaemic stroke. European and US guidelines for …
fundamental part in the occurence of ischaemic stroke. European and US guidelines for …
Going deep in medical image analysis: concepts, methods, challenges, and future directions
Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …
technology has recently attracted so much interest of the Medical Imaging Community that it …
A survey of deep-learning applications in ultrasound: Artificial intelligence–powered ultrasound for improving clinical workflow
Ultrasound is the most commonly used imaging modality in clinical practice because it is a
nonionizing, low-cost, and portable point-of-care imaging tool that provides real-time …
nonionizing, low-cost, and portable point-of-care imaging tool that provides real-time …
[HTML][HTML] State-of-the-art review on deep learning in medical imaging
Deep learning (DL) is affecting each and every sphere of public and private lives and
becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the …
becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the …
Applications of artificial intelligence in cardiology. The future is already here
PI Dorado-Díaz, J Sampedro-Gómez… - Revista Española de …, 2019 - Elsevier
There is currently no other hot topic like the ability of current technology to develop
capabilities similar to those of human beings, even in medicine. This ability to simulate the …
capabilities similar to those of human beings, even in medicine. This ability to simulate the …
Image segmentation using computational intelligence techniques
Image segmentation methodology is a part of nearly all computer schemes as a pre-
processing phase to excerpt more meaningful and useful information for analysing the …
processing phase to excerpt more meaningful and useful information for analysing the …
Deep learning in omics data analysis and precision medicine
J Martorell-Marugán, S Tabik… - Exon …, 2019 - exonpublications.com
The rise of omics techniques has resulted in an explosion of molecular data in modern
biomedical research. Together with information from medical images and clinical data, the …
biomedical research. Together with information from medical images and clinical data, the …
Rheumatoid arthritis: atherosclerosis imaging and cardiovascular risk assessment using machine and deep learning–based tissue characterization
Abstract Purpose of the Review Rheumatoid arthritis (RA) is a chronic, autoimmune disease
which may result in a higher risk of cardiovascular (CV) events and stroke. Tissue …
which may result in a higher risk of cardiovascular (CV) events and stroke. Tissue …