UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 6
June-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2106145


Registration ID:
310356

Page Number

b25-b35

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Title

LUNG INFECTION DETECTION OF COVID 19 PATIENTS

Abstract

the corona virus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,966,000 people in more than 200 countries and territories as of October, 2020. Detecting COVID-19 at early stage is essential to deliver proper healthcare to the patients and also to protect the uninfected population. To this end, we develop a framework to automatically diagnose COVID-19 from the community acquired pneumonia (CAP) in chest computed tomography (CT). In particular, we propose a Noise Robust Segmentation approach with a recurrent neural network (RNN) to focus on the infection regions in lungs when making decisions of diagnoses. Note that there exists imbalanced distribution of the sizes of the infection regions between COVID-19 and CAP, partially due to fast progress of COVID-19 after symptom onset. Our framework is evaluated upon the largest multi-center CT data for COVID-19 from hospitals.

Key Words

COVID-19, Deep Learning, Recurrent neural network, noisy label, segmentation, pneumonia.

Cite This Article

"LUNG INFECTION DETECTION OF COVID 19 PATIENTS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.b25-b35, June-2021, Available :http://www.jetir.org/papers/JETIR2106145.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"LUNG INFECTION DETECTION OF COVID 19 PATIENTS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppb25-b35, June-2021, Available at : http://www.jetir.org/papers/JETIR2106145.pdf

Publication Details

Published Paper ID: JETIR2106145
Registration ID: 310356
Published In: Volume 8 | Issue 6 | Year June-2021
DOI (Digital Object Identifier):
Page No: b25-b35
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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