Author: Degerli, Aysen; Ahishali, Mete; Kiranyaz, Serkan; Chowdhury, Muhammad E. H.; Gabbouj, Moncef
Title: Reliable COVID-19 Detection Using Chest X-ray Images Cord-id: fz8gk12f Document date: 2021_1_28
ID: fz8gk12f
Snippet: Coronavirus disease 2019 (COVID-19) has emerged the need for computer-aided diagnosis with automatic, accurate, and fast algorithms. Recent studies have applied Machine Learning algorithms for COVID-19 diagnosis over chest X-ray (CXR) images. However, the data scarcity in these studies prevents a reliable evaluation with the potential of overfitting and limits the performance of deep networks. Moreover, these networks can discriminate COVID-19 pneumonia usually from healthy subjects only or occa
Document: Coronavirus disease 2019 (COVID-19) has emerged the need for computer-aided diagnosis with automatic, accurate, and fast algorithms. Recent studies have applied Machine Learning algorithms for COVID-19 diagnosis over chest X-ray (CXR) images. However, the data scarcity in these studies prevents a reliable evaluation with the potential of overfitting and limits the performance of deep networks. Moreover, these networks can discriminate COVID-19 pneumonia usually from healthy subjects only or occasionally, from limited pneumonia types. Thus, there is a need for a robust and accurate COVID-19 detector evaluated over a large CXR dataset. To address this need, in this study, we propose a reliable COVID-19 detection network: ReCovNet, which can discriminate COVID-19 pneumonia from 14 different thoracic diseases and healthy subjects. To accomplish this, we have compiled the largest COVID-19 CXR dataset: QaTa-COV19 with 124,616 images including 4603 COVID-19 samples. The proposed ReCovNet achieved a detection performance with 98.57% sensitivity and 99.77% specificity.
Search related documents:
Co phrase search for related documents- accurate evaluation and low quality: 1
- acid detection and acute respiratory syndrome: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- acid detection and low quality: 1, 2
- activation function and acute respiratory syndrome: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19
- activation function and loss function: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
- activation function and low quality: 1
- activation map and acute respiratory syndrome: 1, 2
- acute respiratory syndrome and loss function: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- acute respiratory syndrome and low quality: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- acute respiratory syndrome and low quality image: 1
- acute respiratory syndrome and lung segmentation: 1, 2, 3, 4, 5
- loss function and low level feature: 1
- loss function and low quality: 1, 2, 3, 4, 5
- loss function and lung segmentation: 1, 2, 3, 4, 5, 6
- low quality and lung segmentation: 1
Co phrase search for related documents, hyperlinks ordered by date