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Image Processing Results of One Week Covid-19 Evolution Pneumonia X-Rays
  • Abhishek Bansal
Abhishek Bansal

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This paper presents the collection of 385 new images and results, obtained after performing many known image processing algorithms and digital image transformations techniques like adding noises namely Gaussian with variances, Poisson and speckle with variances; double precision, methods of Sobel, Prewitt and Robert; dehazing algorithm, pixel intensities, vector quantization, k-means clustering, fuzzy logic and morphological segmentation. Images used in this paper are five X-Rays at day 0, day3, day 4 and day 6, which are Posterior to Anterior (PA) views of the patient’s lungs who was diagnosed with covid-19 Pneumonia. All results are included in the paper as well as separate images have also been uploaded on the open-access page. The data has been analyzed with histogram and mathematical polynomial fitting equations and matrices have been also submitted which can used in the digital testing of machines or computer diagnostic solutions. As these results reveal certain patterns, these further processed X-Ray results can help researchers or doctors in understanding ailment or diagnosing and to pharmacologists in making medicine or machine/therapy.