Author: Aboul Ella Hassanien; Lamia Nabil Mahdy; Kadry Ali Ezzat; Haytham H. Elmousalami; Hassan Aboul Ella
Title: Automatic X-ray COVID-19 Lung Image Classification System based on Multi-Level Thresholding and Support Vector Machine Document date: 2020_4_6
ID: 45dpoepu_26
Snippet: The proposed system starts by visualizing a patient's X-ray lung image and applying a median filter to enhance the contrast of the input images. Then, a multi-level image segmentation threshold based on Otsu objective function is applied. Then, the support vector machine has applied to classify the infected lung from non-infected. The overall procedures are described in detail in the following section along with the steps for each process. The ov.....
Document: The proposed system starts by visualizing a patient's X-ray lung image and applying a median filter to enhance the contrast of the input images. Then, a multi-level image segmentation threshold based on Otsu objective function is applied. Then, the support vector machine has applied to classify the infected lung from non-infected. The overall procedures are described in detail in the following section along with the steps for each process. The overall architecture of the proposed COVID-19 classification system is described in Figure 2 . is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
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