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Total 123 results found since Jan 2013.

Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA
DISCUSSION: Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.PMID:37289978 | DOI:10.1002/alz.13346
Source: The Journal of Alzheimers Association - June 8, 2023 Category: Psychiatry Authors: Paul N Jensen Tanweer Rashid Jeffrey B Ware Yuhan Cui Colleen M Sitlani Thomas R Austin W T Longstreth Alain G Bertoni Elizabeth Mamourian R Nick Bryan Ilya M Nasrallah Mohamad Habes Susan R Heckbert Source Type: research

What Are the Classifications of Perinatal Stroke?
Discussion Perinatal stroke occurs in about 1:1000 live births and is a “focal vascular injury from the fetal period to 28 days postnatal age.” Perinatal stroke is the most common cause of hemiparetic cerebral palsy and causes other significant morbidity including cognitive deficits, learning disabilities, motor problems, sensory problems including visual and hearing disorders, epilepsy, and behavioral and psychological problems. Family members are also affected because of the potential anxiety and guilt feelings that having a child with a stroke presents, along with the care that may be needed over the child&#...
Source: PediatricEducation.org - May 1, 2023 Category: Pediatrics Authors: Pediatric Education Tags: Uncategorized Source Type: news

Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm
CONCLUSION: The evaluations in this work have demonstrated that this methodology produces acceptable results for classifying magnetic resonance imaging (MRI) data.PMID:36910524 | PMC:PMC9998982 | DOI:10.3389/fcvm.2023.1101765
Source: Atherosclerosis - March 13, 2023 Category: Cardiology Authors: Ya-Fang Chen Zhen-Jie Chen You-Yu Lin Zhi-Qiang Lin Chun-Nuan Chen Mei-Li Yang Jin-Yin Zhang Yuan-Zhe Li Yi Wang Yin-Hui Huang Source Type: research

A survey of deep learning for MRI brain tumor segmentation methods: Trends, challenges, and future directions
ConclusionThis review's objective is to increase scholars' interest in this difficult field and familiarize them with current advancements in it. To create CAD systems aimed at brain tumor identification using MR images, digital image processing approaches, such as preprocessing, segmentation, and classification, are applied. The classic machine learning and deep learning approaches for brain tumor identification are deliberated in this work. This paper provides a summary of commonly used MR image datasets. For classification, various machine learning and deep learning algorithms have been used. This survey examines curren...
Source: Health and Technology - February 27, 2023 Category: Information Technology Source Type: research

MRI for all: Cheap portable scanners aim to revolutionize medical imaging
.news-article__hero--featured .parallax__element{ object-position: 47% 50%; -o-object-position: 47% 50%; } The patient, a man in his 70s with a shock of silver hair, lies in the neuro intensive care unit (neuro ICU) at Yale New Haven Hospital. Looking at him, you’d never know that a few days earlier a tumor was removed from his pituitary gland. The operation didn’t leave a mark because, as is standard, surgeons reached the tumor through his nose. He chats cheerfully with a pair of research associates who have come to check his progress with a new and potentially revolutionary device they are testing. The cylind...
Source: Science of Aging Knowledge Environment - February 23, 2023 Category: Geriatrics Source Type: research

Your native tongue holds a special place in your brain, even if you speak 10 languages
This study “contributes to our understanding of how our brain learns new things,” says Augusto Buchweitz, a cognitive neuroscientist at the University of Connecticut, Storrs, who was not involved in the work. “The earlier you learn something, the more your brain [adapts] and probably uses less resources.” Scientists have largely ignored what’s going on inside the brains of polyglots—people who speak more than five languages—says Ev Fedorenko, a cognitive neuroscientist at the Massachusetts Institute of Technology who led the new study. “There’s oodles of work on individuals whose language systems are...
Source: Science of Aging Knowledge Environment - February 3, 2023 Category: Geriatrics Source Type: research

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease
Stroke is a major cause of death or disability. As imaging-based patient stratification improves acute stroke therapy, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is of major interest in image brain perfusion. However, expert-level perfusion maps require a manual or semi-manual post-processing by a medical expert making the procedure time-consuming and less-standardized. Modern machine learning methods such as generative adversarial networks (GANs) have the potential to automate the perfusion map generation on an expert level without manual validation. We propose a modified pix2pix GAN with a tempo...
Source: Frontiers in Neurology - January 10, 2023 Category: Neurology Source Type: research

Prognosis of ischemic stroke predicted by machine learning based on multi-modal MRI radiomics
ConclusionThe ML models based on muti-modal MRI radiomics are of high value for predicting clinical outcomes in acute stroke patients.
Source: Frontiers in Psychiatry - January 9, 2023 Category: Psychiatry Source Type: research

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning
CONCLUSION: The ischemic core volumes calculated by the described ML approach on NCCT approximate those obtained by MRI in patients with AIS who present beyond 1 hour from stroke onset.PMID:36572984 | DOI:10.1177/15910199221145487
Source: Interventional Neuroradiology - December 27, 2022 Category: Radiology Authors: Iris E Chen Brian Tsui Haoyue Zhang Joe X Qiao William Hsu May Nour Noriko Salamon Luke Ledbetter Jennifer Polson Corey Arnold Mersedeh BahrHossieni Reza Jahan Gary Duckwiler Jeffrey Saver David Liebeskind Kambiz Nael Source Type: research

Deep Learning in Ischemic Stroke Imaging Analysis: A Comprehensive Review
Biomed Res Int. 2022 Nov 14;2022:2456550. doi: 10.1155/2022/2456550. eCollection 2022.ABSTRACTIschemic stroke is a cerebrovascular disease with a high morbidity and mortality rate, which poses a serious challenge to human health and life. Meanwhile, the management of ischemic stroke remains highly dependent on manual visual analysis of noncontrast computed tomography (CT) or magnetic resonance imaging (MRI). However, artifacts and noise of the equipment as well as the radiologist experience play a significant role on diagnostic accuracy. To overcome these defects, the number of computer-aided diagnostic (CAD) methods for i...
Source: Biomed Res - November 24, 2022 Category: Research Authors: Liyuan Cui Zhiyuan Fan Yingjian Yang Rui Liu Dajiang Wang Yingying Feng Jiahui Lu Yifeng Fan Source Type: research