Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification-Reference-Cited by-同舟云学术

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Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification

Published:2023-11-27 Issue: Volume: Page:163-177
ISSN:0302-9743
Container-title:Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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Author:

F. Roberto Guilherme,C. Pereira Danilo,S. Martins Alessandro,A. A. Tosta Thaína,Soares Carlos,Lumini Alessandra,B. Rozendo Guilherme,A. Neves Leandro,Z. Nascimento Marcelo

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-49018-7_12

Reference30 articles.

1. Bandirali, M., et al.: Chest radiograph findings in asymptomatic and minimally symptomatic quarantined patients in codogno, italy during covid-19 pandemic. Radiology 295(3), E7–E7 (2020)

2. Căliman, A., Ivanovici, M.: Psoriasis image analysis using color lacunarity. In: 2012 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), pp. 1401–1406. IEEE (2012)

3. Chihara, T.S.: An introduction to orthogonal polynomials. Courier Corporation (2011)

4. Corman, V.M., et al.: Detection of 2019 novel coronavirus (2019-ncov) by real-time rt-pcr. Eurosurveillance 25(3), 2000045 (2020)

5. Cozzi, D., et al.: Chest x-ray in new coronavirus disease 2019 (covid-19) infection: findings and correlation with clinical outcome. Radiol. Med. (Torino) 125, 730–737 (2020)

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