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Early COVID-19 Diagnosis from Lung Ultrasound Images Combining RIULBP-TP and 3D-DenseNet

The pandemic of COVID-19 has affected the world with the high deaths rate. Early diagnosis of this disease is the bottleneck to the patient's health recovery. Its symptoms appear through the wide range of experiments especially accompany with the severe lung lesions. These lesions could be spot...

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Main Authors: Esmaeili, Vida, Feghhi, Mahmood Mohassel, Omid Shahdi, Seyed
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creator Esmaeili, Vida
Feghhi, Mahmood Mohassel
Omid Shahdi, Seyed
description The pandemic of COVID-19 has affected the world with the high deaths rate. Early diagnosis of this disease is the bottleneck to the patient's health recovery. Its symptoms appear through the wide range of experiments especially accompany with the severe lung lesions. These lesions could be spotted on the lung ultrasound data. Being non-intrusive, low cost, portable, and accurate enough are among the main pros of ultrasound imaging. However, this imaging modality most often contain variety of noises. In order to overcome this challenge, we propose a novel approach combining Rotation Invariant Uniform LBP on 3 Planes (RIULBP-TP) and 3D-DenseNet. These methods are proved to be robust against various noises. Accordingly, our method reaches outstanding results comparing to related most state-of-the-art methods.
doi_str_mv 10.1109/CFIS54774.2022.9756430
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ispartof 2022 9th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS), 2022, p.1-5
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subjects 3D-DenseNet
Costs
COVID-19
Imaging
Lesions
Lung
lung ultrasound data
Pandemics
RIULBP-TP
Ultrasonic imaging
title Early COVID-19 Diagnosis from Lung Ultrasound Images Combining RIULBP-TP and 3D-DenseNet
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