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Specialty: Radiology
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Total 224 results found since Jan 2013.

Use of Machine Learning Algorithms to Predict the Outcomes of Mechanical Thrombectomy in Acute Ischemic Stroke Patients With an Extended Therapeutic Time Window
Conclusions Machine learning algorithms may facilitate prediction of 90-day functional outcomes in AIS patients with an extended therapeutic time window.
Source: Journal of Computer Assisted Tomography - September 1, 2022 Category: Radiology Tags: Neuroimaging: Brain Source Type: research

Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study
ConclusionsWith the assistance of our proposed DL model, radiologists got better performance in the detection of AIS lesions on NCCT.
Source: Insights into Imaging - December 6, 2022 Category: Radiology Source Type: research

A clinical –radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study
ConclusionThe proposed clinical –radiomics model is a dependable approach that could provide risk assessment of HT for patients who receive IVT after stroke.
Source: Insights into Imaging - March 29, 2023 Category: Radiology Source Type: research

Can Shape Analysis Differentiate Free-floating Internal Carotid Artery Thrombus from Atherosclerotic Plaque in Patients Evaluated with CTA for Stroke or Transient Ischemic Attack?
Conclusions: We identified five quantitative shape descriptors of carotid FFT. This shape “signature” shows potential for supplementing conventional lesion characterization in cases of suspected FFT.
Source: Academic Radiology - February 8, 2014 Category: Radiology Authors: Rebecca E. Thornhill, Cheemun Lum, Arash Jaberi, Pawel Stefanski, Carlos H. Torres, Franco Momoli, William Petrcich, Dar Dowlatshahi Tags: Original Investigations 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

Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot Study
ConclusionDL models may aid in the prediction of functional thrombolysis outcomes. Further investigation with larger datasets and additional imaging sequences is indicated.
Source: Academic Radiology - May 2, 2019 Category: Radiology Source Type: research

White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts – The MRI-GENIE study
Publication date: Available online 29 May 2019Source: NeuroImage: ClinicalAuthor(s): Markus D. Schirmer, Adrian V. Dalca, Ramesh Sridharan, Anne-Katrin Giese, Kathleen L. Donahue, Marco J. Nardin, Steven J.T. Mocking, Elissa C. McIntosh, Petrea Frid, Johan Wasselius, John W. Cole, Lukas Holmegaard, Christina Jern, Jordi Jimenez-Conde, Robin Lemmens, Arne G. Lindgren, James F. Meschia, Jaume Roquer, Tatjana Rundek, Ralph L. SaccoAbstractWhite matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS)....
Source: NeuroImage: Clinical - May 29, 2019 Category: Radiology Source Type: research

Abstract No. 720 Identification of irreversibly damaged brain tissue on computed tomography perfusion using convolutional neural network to assist selection for mechanical thrombectomy in ischemic stroke patients
Endovascular treatment of ischemic stroke has shown positive clinical outcomes. Further optimization requires identifying patients who will benefit from reperfusion. We propose using deep learning, specifically 3D convolutional neural networks (CNN), to identify infarcted tissue (core) on CT perfusion (CTP) with diffusion weighted imaging (DWI) MRI as gold standard for irreversible brain infarction and evaluate lesion size impact on the network ’s performance.
Source: Journal of Vascular and Interventional Radiology : JVIR - February 20, 2020 Category: Radiology Authors: R. Wang, K. Chang, H. Zhou, J. Wu, G. Cohan, M. Jayaraman, R. Huang, J. Boxerman, L. Yang, F. Hui, J. Woo, H. Bai Tags: Scientific Traditional Poster Source Type: research

Machine learning volumetry of ischemic brain lesions on CT after thrombectomy —prospective diagnostic accuracy study in ischemic stroke patients
ConclusionNCCT ILV measured automatically by the Brainomix software might be considered a valuable radiological outcome measure.
Source: Neuroradiology - April 21, 2020 Category: Radiology Source Type: research

Deep symmetric three-dimensional convolutional neural networks for identifying acute ischemic stroke via diffusion-weighted images
CONCLUSIONS: DeepSym-3D-CNN is a potential method for automatically identifying AIS via DWI images and can be extended to other diseases with asymmetric lesions.PMID:33967077 | DOI:10.3233/XST-210861
Source: Journal of X-Ray Science and Technology - May 10, 2021 Category: Radiology Authors: Liyuan Cui Shanhua Han Shouliang Qi Yang Duan Yan Kang Yu Luo Source Type: research