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Covid19 Detection Using Chest X-ray Images Along with Corresponding Metadata of the Chest X-ray

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Abstract

COVID-19 is reported as a very infectious which is increasing in rapid speed at present time. In this pandemic World health organization (WHO) is monitoring the situation and providing the preventive measures coordinating the treatment strategies to fight against Covid-19 through out the world. The only way to stop the further spread of this is to detect the disease early. Some works have been started to investigate covid19 using Deep learning algorithm over chestX-ray (CXR) images. In our work we have processed one CNN model which can process CXR images along with the metadata(non imaging data) available with the dataset to classify Covid 19. Resnet 50, Dense net 121, Mobile Net,VGG-16, Inception-V3 and one proposed Convolution Neural Network have been modified to accept the metadata along with CXR image. Some state of the art Deep learning models have been run to classify the covid 19 on the same data set and compared with our best model. Experiments have been done in two phases. In the 1st phase we used CNN models on CXR image only and in the 2nd phase we ran all modified CNN models over the same CXR images with their matadata. The experimental results shows that the output of 2nd phase out performs the output of 1st phase.After that we compared our best model (Proposed CNN) with other state of art models.

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Data availability

The datasets generated during the current study are not publicly available because a new dataset have been developed after taking the data from (1) COVID-19 chest xray | Kaggle and (2) [1705.02315] ChestX-ray8: Hospital-scale ChestX-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases (arxiv.org)

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript

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Author notes

  1. Ranjita Das and Bipal Khanal contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science & Engineering, Sikkim Manipal Institute of Technolog, Sikkim Manipal University, Majhitar, Gangtok, East Sikkim, 737136, India

    Sourav Paul & Bipal Khanal

  2. Department of Computer Science & Engineering, NIT, Chaltlang, Aizawl, Mizoram, 796012, India

    Sourav Paul

  3. Department of Computer Science & Engineering, NIT, Agartala, Tripura, 799046, India

    Ranjita Das

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  1. Sourav Paul
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Correspondence to Ranjita Das.

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Paul, S., Das, R. & Khanal, B. Covid19 Detection Using Chest X-ray Images Along with Corresponding Metadata of the Chest X-ray. Wireless Pers Commun (2024). https://doi.org/10.1007/s11277-024-11171-7

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