Cad Systems for Automatic Detection and Classification of Covid19 Using Image Processing and Machine Learning

Ajesh F; Felix Philip; Priya Sajan; Robbi Rahim

Proceedings of the 2nd Biennial International Conference on Safe Community, B-ICSC 2022, 20-21 September 2022, Bandar Lampung, Lampung, Indonesia

Research Article

Cad Systems for Automatic Detection and Classification of Covid19 Using Image Processing and Machine Learning

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@INPROCEEDINGS{10.4108/eai.20-9-2022.2334191,
    author={Ajesh F and Felix M Philip and Priya P Sajan and Robbi Rahim},
    title={Cad Systems for Automatic Detection and Classification of Covid19 Using Image Processing and Machine Learning},
    proceedings={Proceedings of the 2nd Biennial International Conference on Safe Community, B-ICSC 2022, 20-21 September 2022, Bandar Lampung, Lampung, Indonesia},
    publisher={EAI},
    proceedings_a={B-ICSC},
    year={2023},
    month={9},
    keywords={covid-19 blood cells platelet count cnn classifier bovm svm ann},
    doi={10.4108/eai.20-9-2022.2334191}
}

Ajesh F
Felix M Philip
Priya P Sajan
Robbi Rahim
Year: 2023
Cad Systems for Automatic Detection and Classification of Covid19 Using Image Processing and Machine Learning
B-ICSC
EAI
DOI: 10.4108/eai.20-9-2022.2334191

Ajesh F¹^,*, Felix M Philip², Priya P Sajan³, Robbi Rahim⁴

1: Associate Professor, Department of Computer Science and Engineering, Sree Buddha College of Engineering, Alappuzha, Kerala India
2: Assistant Professor, Department of Computer Science and information Technology, JAIN (Deemed University), Kochi, Kerala, India
3: Project Engineer,C-DAC, Trivandrum, Kerala, India
4: Sekolah Tinggi llmu Manajemen Sukma, Medan, Imdonesia

*Contact email: ajeshf@gmail.com

Abstract

Counting of platelets in blood cells assumes to be a significant role in the health sector. In any case, the procedure of the manual tallying of platelets in blood cells is incredibly tedious, which prompts erroneous outcomes. So as to overcome these difficulties, this research presents a fully automated software solution, enriched with image processing and machine learning techniques to distinguish and to count the number of RBC, WBC and Platelets cells in the sample blood images and to classify the different types of viruses present in it. Several problems and missing features in existing white blood cell classifiers were addressed by implementing an effusively automated method using a multiclass classifier.

Keywords: covid-19 blood cells platelet count cnn classifier bovm svm ann

Published: 2023-09-04
Publisher: EAI

: http://dx.doi.org/10.4108/eai.20-9-2022.2334191