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Total 224 results found since Jan 2013.

CT matches MRI for late-window stroke evaluation
Stroke patients who underwent endovascular therapy had similar improvement...Read more on AuntMinnie.comRelated Reading: Machine learning can predict stroke treatment outcomes Study reveals steep cost of delaying stroke treatment 3 CTA signs show which stroke patients can skip surgery Perfusion imaging expands window for stroke treatment CTA helps direct use of clot removal for stroke patients
Source: AuntMinnie.com Headlines - February 6, 2019 Category: Radiology Source Type: news

Women less likely to receive poststroke imaging
Women who have experienced ischemic stroke are less likely than men to be evaluated...Read more on AuntMinnie.comRelated Reading: Start-up BURL develops ultrasound-based 'ECG for stroke' Machine learning can predict stroke treatment outcomes Medical groups urge endovascular training for stroke 3 CTA signs show which stroke patients can skip surgery Northwestern Medicine hastens stroke care with mobile CT unit
Source: AuntMinnie.com Headlines - January 31, 2019 Category: Radiology Source Type: news

AI reveals cause of transient ischemic attack symptoms
An artificial intelligence (AI) algorithm that analyzed free text in patient...Read more on AuntMinnie.comRelated Reading: New algorithm overcomes imaging AI challenges Machine learning can predict stroke treatment outcomes Medical groups urge endovascular training for stroke Key MRI markers link vascular brain injury to health risks AI can prescreen head CT studies for urgent findings
Source: AuntMinnie.com Headlines - January 29, 2019 Category: Radiology Source Type: news

Improving Sensitivity on Identification and Delineation of Intracranial Hemorrhage Lesion Using Cascaded Deep Learning Models
AbstractHighly accurate detection of the intracranial hemorrhage without delay is a critical clinical issue for the diagnostic decision and treatment in an emergency room. In the context of a study on diagnostic accuracy, there is a tradeoff between sensitivity and specificity. In order to improve sensitivity while preserving specificity, we propose a cascade deep learning model constructed using two convolutional neural networks (CNNs) and dual fully convolutional networks (FCNs). The cascade CNN model is built for identifying bleeding; hereafter the dual FCN is to detect five different subtypes of intracranial hemorrhage...
Source: Journal of Digital Imaging - January 24, 2019 Category: Radiology Source Type: research

Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning FUNCTIONAL
CONCLUSIONS: The proposed automated ASPECTS scoring approach shows reasonable ability to determine ASPECTS on NCCT images in patients presenting with acute ischemic stroke.
Source: American Journal of Neuroradiology - January 11, 2019 Category: Radiology Authors: Kuang, H., Najm, M., Chakraborty, D., Maraj, N., Sohn, S. I., Goyal, M., Hill, M. D., Demchuk, A. M., Menon, B. K., Qiu, W. Tags: FUNCTIONAL Source Type: research

Machine learning studies on major brain diseases: 5-year trends of 2014 –2018
AbstractIn the recent 5  years (2014–2018), there has been growing interest in the use of machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic lesion changes within the area of neuroradiology. However, to date, the majority of research trend and current status have not been clearly il luminated in the neuroradiology field. More than 1000 papers have been published during the past 5 years on subject classification and prediction focused on multiple brain disorders. We provide a survey of 209 papers in this field with a focus on top ten active areas of research; i.e., Alzheimer’ s di...
Source: Japanese Journal of Radiology - November 29, 2018 Category: Radiology Source Type: research

Simultaneous NODDI and GFA parameter map generation from subsampled q ‐space imaging using deep learning
ConclusionsEstimates of NODDI and GFA parameters estimated simultaneously with a deep learning network from highly undersampled q ‐space data were improved compared to other state‐of‐the‐art methods providing a 10‐fold reduction scan time compared to conventional methods.
Source: Magnetic Resonance in Medicine - November 13, 2018 Category: Radiology Authors: Eric K. Gibbons, Kyler K. Hodgson, Akshay S. Chaudhari, Lorie G. Richards, Jennifer J. Majersik, Ganesh Adluru, Edward V.R. DiBella Tags: FULL PAPER Source Type: research

Simultaneous NODDI and GFA parameter map generation from subsampled q-space imaging using deep learning.
CONCLUSIONS: Estimates of NODDI and GFA parameters estimated simultaneously with a deep learning network from highly undersampled q-space data were improved compared to other state-of-the-art methods providing a 10-fold reduction scan time compared to conventional methods. PMID: 30426558 [PubMed - as supplied by publisher]
Source: Magnetic Resonance in Medicine - November 13, 2018 Category: Radiology Authors: Gibbons EK, Hodgson KK, Chaudhari AS, Richards LG, Majersik JJ, Adluru G, DiBella EVR Tags: Magn Reson Med Source Type: research

Machine learning can predict stroke treatment outcomes
Making use of imaging features and demographic information, machine-learning...Read more on AuntMinnie.comRelated Reading: 5 reasons why imaging AI is different from CAD Deep learning improves detection of cerebral aneurysms ASTRO: AI's rad therapy future is in predicting outcomes AI effective for assessing breast density AI can prescreen head CT studies for urgent findings
Source: AuntMinnie.com Headlines - October 30, 2018 Category: Radiology Source Type: news

Functional connectivity analysis for thalassemia disease based on a graphical lasso model.
FUNCTIONAL CONNECTIVITY ANALYSIS FOR THALASSEMIA DISEASE BASED ON A GRAPHICAL LASSO MODEL. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:1295-1298 Authors: Coloigner J, Phlypo R, Bush A, Lepore N, Wood J Abstract Thalassemia is a congenital disorder of hemoglobin synthesis which can lead to thromboembolic events and stroke in the brain. In this work we propose to use a functional connectivity model to discriminate between control and diseased subjects. Our connectivity measure is based on functional magnetic resonance imaging, and hence common variations of the blood oxygenation level in spatially d...
Source: Proceedings - International Symposium on Biomedical Imaging - October 24, 2018 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Use of Gradient Boosting Machine Learning to Predict Patient Outcome in Acute Ischemic Stroke on the Basis of Imaging, Demographic, and Clinical Information
American Journal of Roentgenology, Ahead of Print.
Source: American Journal of Roentgenology - October 24, 2018 Category: Radiology Authors: Yuan Xie Bin Jiang Enhao Gong Ying Li Guangming Zhu Patrik Michel Max Wintermark Greg Zaharchuk Source Type: research

Ultrasound imaging gauges muscle tightness after stroke
Ultrasound strain imaging can be an effective tool for assessing poststroke...Read more on AuntMinnie.comRelated Reading: MRI links lifestyle factors to stroke, dementia risk 5 risk factors help predict brain hemorrhage on CT AI algorithm can triage head CT exams for urgent review Ultrasound elastography helps identify invasive breast cancer AIUM: Can deep learning classify liver fibrosis on US?
Source: AuntMinnie.com Headlines - August 22, 2018 Category: Radiology Source Type: news

Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT score (ASPECTS) in the clinical routine
ConclusionFor ASPECTS assessment, the examined software may provide valid data in case of normal brain. It may enhance the work of neuroradiologists in clinical decision making. A final human check for plausibility is needed, particularly in patient groups with pre-existing cerebral changes.
Source: Neuroradiology - July 31, 2018 Category: Radiology Source Type: research

Parent Artery Reconstruction for Large or Giant Cerebral Aneurysms Using the Tubridge Flow Diverter: A Multicenter, Randomized, Controlled Clinical Trial (PARAT) INTERVENTIONAL
CONCLUSIONS: This trial showed an obviously higher rate of large and giant aneurysm obliteration with the Tubridge FD over Enterprise stent-assisted coiling. However, this higher obliteration rate came at the cost of a nonsignificantly higher rate of complications. Investigational site comparisons suggested that a learning curve for flow-diverter implantation should be recognized and factored into trial designs.
Source: American Journal of Neuroradiology - May 15, 2018 Category: Radiology Authors: Liu, J.- m., Zhou, Y., Li, Y., Li, T., Leng, B., Zhang, P., Liang, G., Huang, Q., Yang, P.- f., Shi, H., Zhang, J., Wan, J., He, W., Liang, C., Zhu, G., Xu, Y., Hong, B., Yang, X., Bai, W., Tian, Y., Zhang, H., Li, Z., Li, Q., Zhao, R., Fang, Y., Zhao, K. Tags: INTERVENTIONAL Source Type: research