Mucormycosis Image classification based on the severity by using Convolutional Neural Network(CNN)

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C.Sugunadevi, Dr.I.Manimozhi, Neha Gopal


Mucormycosis is a rare deadly disease, it is one of the serious fungal infections caused by the fungus called Mucormycetes. Mucormycosis lives everywhere in the environment, if a person has less immunity, (ie) affected with covid-19 before some time, or with the diabetes are likely to be affected quickly, if it enters through the nose, sinus or through the lungs, causes a deadly problem by affecting the eyes and spreads towards the brain rapidly. The purpose of this paper is to classify the images by constructing a Machine Learning - Convolutional Neural Network based on the severity of the symptoms, (whether the symptom is mild or severe) it was accomplished by training and validating/testing the Neural Network by loading the given Dataset. In addition, Image Data Generator is used to build this neural network. The proposed model was coded in python and tested in Jupyter Notebook considering 18 images, the accuracy percentage was 100%.  Considering 143 images, the accuracy percentage was 97%. Considering 520 images, the accuracy percentage was 97%.

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