2021
DOI: 10.1007/978-3-030-67716-9_8
|View full text |Cite
|
Sign up to set email alerts
|

Feature Based Automated Detection of COVID-19 from Chest X-Ray Images

Abstract: Nowadays the biggest challenge for health care is controlling the pandemic of Coronavirus disease 2019 . Radiological investigation combining with machine learning can serve as a standardized methodology for detecting COVID-19. Chest X-ray imaging is the most feasible radiological test for COVID-19. Machine learning-based automated classification of COVID-19 from chest X-ray images can act as an assistive method to the medical experts for accurate diagnosis of disease. Aiming at this, the study focused on deve… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
2
0
1

Year Published

2022
2022
2024
2024

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(3 citation statements)
references
References 30 publications
0
2
0
1
Order By: Relevance
“…Dissimilar geometry structures, shapes, and sizes are present in each COVID-19 infected image for different levels of infections. From the previous works [29][30][31][32], we understand that the shape descriptors such as Zernike and Hu moments [24] are good enough to define detailed shape information, especially for medical images (CT images or X-ray images). A good shape descriptor should provide the following: High discrimination ability with low redundancy; Be invariant to scale, rotation, and translation; and Provide both coarse to finer detailed representation.…”
Section: Zernike Moment Feature (Zmf) For Shape Descriptors and 2-gra...mentioning
confidence: 99%
See 1 more Smart Citation
“…Dissimilar geometry structures, shapes, and sizes are present in each COVID-19 infected image for different levels of infections. From the previous works [29][30][31][32], we understand that the shape descriptors such as Zernike and Hu moments [24] are good enough to define detailed shape information, especially for medical images (CT images or X-ray images). A good shape descriptor should provide the following: High discrimination ability with low redundancy; Be invariant to scale, rotation, and translation; and Provide both coarse to finer detailed representation.…”
Section: Zernike Moment Feature (Zmf) For Shape Descriptors and 2-gra...mentioning
confidence: 99%
“…However, when, T = 0.15, the reported sensitivity and specificity were 96% and 70.6%, respectively. COVID-19 infection detection through the feature extraction method and classification model is discussed in [24], Bardhan et al, 2021. In feature extraction, the total number of 55 texture features are gathered from Xray images used for training and testing. The features are classified in the COVID-19 region using four standard classification models.…”
Section: Covid-19 Related Work Using Ai Techniquesmentioning
confidence: 99%
“…No contexto de imagens pulmonares relacionadas ao COVID-19 e de imagens de ultrassom para identificação de tumores em mamas, as características de textura têm sido amplamente utilizadas (BENAOUALI et al, 2022;REZAZADEH;JAFARIAN;KORD, 2022;BARDHAN;ROGA, 2021;PEREIRA et al, 2020). Desta forma, em ambas as bases de imagens adquiridas, foram extraídas características de nove extratores de textura e um extrator de histograma de cinzas que foram abordados na Seção 2.3 e utilizados para experimentos do método desenvolvido nesta pesquisa.…”
Section: Visão Geralunclassified