Covid-19 Detection Using Multimodal Imaging Data
Abstract & Details
Research Area
Computer Science and Engineering
Keywords
Keywords: - COVID-19 Detection
Deep Learning
Convolutional Neural Network
Radiological Imaging
CT
scan
Ultrasound.
Abstract
The COVID-19 pandemic has spread rapidly across the globe and has caused life threating consequences to
mankind ever since it started from Wuhan, China in December 2019. Early Detection and Prevention can help in
containing the spread of the disease. Screening of large number of people is pressing priority. One of the crucial
steps towards achieving this goal is through radiological examination. The approach we followed aims to remove
unwanted noise from images so that the deep learning models can focus on detection of disease. The results prove
that Ultrasound imaging is far more superior than X-Ray and CT scan. In this study, we identify a suitable
Convolutional Neural Network (CNN) model that will detect the Covid-19 Positive patients using chest X-Ray
images. Images of Covid positive and negative patients are divided into trainable images and testing images. This
test can be done on any computer and by any medical examiner or technician to detect COVID-19 in a matter of
few seconds.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Neha G | Dayananda Sagar Academy Of Technology And Management |
| 2 | Rhema Rakshita S | Dayananda Sagar Academy Of Technology And Management |
| 3 | Ayeesha Taneem | Dayananda Sagar Academy Of Technology And Management |
| 4 | Manasa Sandeep | Dayananda Sagar Academy Of Technology And Management |
How to Cite
Use the following formats to cite this article in your research.
APA Style
G, Neha, S, Rhema Rakshita, Taneem, Ayeesha, & Sandeep, Manasa (2021). Covid-19 Detection Using Multimodal Imaging Data. International Journal of Advance Research and Innovative Ideas In Education, 7(3), 3201-3205.
MLA Style
G, Neha, et al. "Covid-19 Detection Using Multimodal Imaging Data." International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 3, 2021, pp. 3201-3205.
IEEE Style
Neha G, Rhema Rakshita S, Ayeesha Taneem, and Manasa Sandeep, "Covid-19 Detection Using Multimodal Imaging Data," International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 3, pp. 3201-3205, 2021.
Vancouver Style
G Neha, S Rhema Rakshita, Taneem Ayeesha, Sandeep Manasa. Covid-19 Detection Using Multimodal Imaging Data. International Journal of Advance Research and Innovative Ideas In Education. 2021;7(3):3201-3205.
Harvard Style
G, Neha, S, Rhema Rakshita, Taneem, Ayeesha, & Sandeep, Manasa (2021) 'Covid-19 Detection Using Multimodal Imaging Data', International Journal of Advance Research and Innovative Ideas In Education, 7(3), pp. 3201-3205.
Chicago Style
G, Neha, et al. "Covid-19 Detection Using Multimodal Imaging Data." International Journal of Advance Research and Innovative Ideas In Education 7, no. 3 (2021): 3201-3205.
Turabian Style
G, Neha, et al. "Covid-19 Detection Using Multimodal Imaging Data." International Journal of Advance Research and Innovative Ideas In Education 7, no. 3 (2021): 3201-3205.
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