Version 1
: Received: 7 April 2021 / Approved: 8 April 2021 / Online: 8 April 2021 (07:12:30 CEST)
Version 2
: Received: 27 April 2021 / Approved: 27 April 2021 / Online: 27 April 2021 (14:08:53 CEST)
How to cite:
Kvak, D.; Kvaková, K. Automatic Detection of Pneumonia in Chest X-Rays using Lobe Deep Residual Network. Preprints2021, 2021040221. https://doi.org/10.20944/preprints202104.0221.v1
Kvak, D.; Kvaková, K. Automatic Detection of Pneumonia in Chest X-Rays using Lobe Deep Residual Network. Preprints 2021, 2021040221. https://doi.org/10.20944/preprints202104.0221.v1
Kvak, D.; Kvaková, K. Automatic Detection of Pneumonia in Chest X-Rays using Lobe Deep Residual Network. Preprints2021, 2021040221. https://doi.org/10.20944/preprints202104.0221.v1
APA Style
Kvak, D., & Kvaková, K. (2021). Automatic Detection of Pneumonia in Chest X-Rays using Lobe Deep Residual Network. Preprints. https://doi.org/10.20944/preprints202104.0221.v1
Chicago/Turabian Style
Kvak, D. and Karolína Kvaková. 2021 "Automatic Detection of Pneumonia in Chest X-Rays using Lobe Deep Residual Network" Preprints. https://doi.org/10.20944/preprints202104.0221.v1
Abstract
One of the critical tools for early detection and subsequent evaluation of the incidence of lung diseases is chest radiography. At a time when the speed and reliability of results, especially for COVID-19 positive patients, is important, the development of applications that would facilitate the work of untrained staff involved in the evaluation is also crucial. Our model takes the form of a simple and intuitive application, into which you only need to upload X-rays: tens or hundreds at once. In just a few seconds, the physician will determine the patient's diagnosis, including the percentage accuracy of the estimate. While the original idea was a mere binary classifier that could tell if a patient was suffering from pneumonia or not, in this paper we present a model that distinguishes between a bacterial disease, a viral infection, or a finding caused by COVID-19. The aim of this research is to demonstrate whether pneumonia can be detected or even spatially localized using a uniform, supervised classification.
Computer Science and Mathematics, Algebra and Number Theory
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
