Automatic arterial input function selection in CT and MR perfusion datasets using deep convolutional neural networks-Reference-Cited by-同舟云学术

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Automatic arterial input function selection in CT and MR perfusion datasets using deep convolutional neural networks

Published:2020-07-18 Issue:9 Volume:47 Page:4199-4211
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Winder Anthony¹²,d’Esterre Christopher D.²³,Menon Bijoy K.¹²³,Fiehler Jens⁴,Forkert Nils D.¹²³⁵

Affiliation:

1. Department of Radiology University of Calgary Calgary Canada

2. Hotchkiss Brain Institute University of Calgary Calgary Canada

3. Department of Clinical Neuroscience University of Calgary Calgary Canada

4. Department of Diagnostic and Interventional Neuroradiology University Medical Center Hamburg‐Eppendorf Hamburg Germany

5. Alberta Children's Hospital Research InstituteUniversity of Calgary Calgary Canada

Funder

Heart and Stroke Foundation of Canada

Canada Research Chairs

Calgary Foundation

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14351

Reference35 articles.

1. Endovascular Therapy in Acute Ischemic Stroke

2. Canadian Stroke Best Practice Recommendations for Acute Stroke Management: Prehospital, Emergency Department, and Acute Inpatient Stroke Care, 6th Edition, Update 2018

3. Thrombectomy 6 to 24 Hours after Stroke with a Mismatch between Deficit and Infarct

4. Thrombectomy for Stroke at 6 to 16 Hours with Selection by Perfusion Imaging

5. 2018 Guidelines for the Early Management of Patients With Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association

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1. Annotation-free prediction of treatment-specific tissue outcome from 4D CT perfusion imaging in acute ischemic stroke;Computerized Medical Imaging and Graphics;2024-06

2. Providing clinical context to the spatio-temporal analysis of 4D CT perfusion to predict acute ischemic stroke lesion outcomes;Journal of Biomedical Informatics;2024-01

3. Core and penumbra estimation using deep learning-based AIF in association with clinical measures in computed tomography perfusion (CTP);Insights into Imaging;2023-09-29

4. Detecting CTP truncation artifacts in acute stroke imaging from the arterial input and the vascular output functions;PLOS ONE;2023-03-30

5. Predicting the tissue outcome of acute ischemic stroke from acute 4D computed tomography perfusion imaging using temporal features and deep learning;Frontiers in Neuroscience;2022-11-04

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