Deep learning-based middle cerebral artery blood flow abnormality detection using flow velocity waveform derived from transcranial Doppler ultrasound-Reference-Cited by-同舟云学术

Deep learning-based middle cerebral artery blood flow abnormality detection using flow velocity waveform derived from transcranial Doppler ultrasound

Published:2023-08 Issue: Volume:85 Page:104882
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Kanti Podder Kanchon,Chowdhury Muhammad E.H.,Al-Maadeed Somaya,Nasrin Nisha Naima,Mahmud Sakib,Hamadelneil Fatema,Almkhlef Taif,Aljofairi Hind,Mushtak Adam,Khandakar Amith,Zughaier Susu

Funder

Qatar University

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference36 articles.

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3. S.G. Thorpe et al., Velocity curvature index: a novel diagnostic biomarker for large vessel occlusion 10(5) (2019) 475–484.

4. F. Wadehn et al., Adaptive maximal blood flow velocity estimation from transcranial doppler echos 8 (2020) 1–11.

5. S.G. Thorpe et al., Toward automated classification of pathological transcranial Doppler waveform morphology via spectral clustering 15(2) (2020) e0228642.

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