Automatic Hemorrhage Detection From Color Doppler Ultrasound Using a Generative Adversarial Network (GAN)-Based Anomaly Detection Method

Automatic Hemorrhage Detection From Color Doppler Ultrasound Using a Generative Adversarial Network (GAN)-Based Anomaly Detection Method

Hemorrhage control has been identified as a priority focus area both for civilian and military populations in the United States because exsanguination is the most common cause of preventable death in hemorrhagic injury. Non-compressible torso hemorrhage (NCTH) has high mortality rate and there are c...

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Bibliographic Details
Main Authors: Jhimli Mitra, Jianwei Qiu, Michael MacDonald, Prem Venugopal, Kirk Wallace, Hossam Abdou, Michael Richmond, Noha Elansary, Joseph Edwards, Neerav Patel, Jonathan Morrison, Luca Marinelli
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Hemorrhage detection
color Doppler ultrasound
unsupervised anomaly detection
generative adversarial network
deep learning
Online Access:https://ieeexplore.ieee.org/document/9863667/

Internet

https://ieeexplore.ieee.org/document/9863667/

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