CNN-Based Chest X-Ray Analysis for Disease Detection

CNN-Based Chest X-Ray Analysis for Disease Detection

Nischith H S1, Dr.T.Ratha Jeyalakshmi 2

1Student, Department of MCA, Dayananda Sagar College of Engineering, Karnataka, India

2Professor & Head, Department of MCA, Dayananda Sagar College of Engineering, Karnataka, India

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Abstract - The process of classifying; detecting and measuring the certainty of lung x-ray image’s abnormality using enhanced complex and deep learning of techniques such as CNN has observed improvements betterment especially to enhance a working solution i.e. pneumonia ,tuberculosis ,COVID-19,lung  cancer. With regard to the datasets, several have been applied in the testing of the model to the utmost extent of its ability as well as its accuracy was well received in passing on the message. Also an intuitive graphical user interface makes it possible for physicians/managers to evaluate x-ray pictures within a short span of time along with exact outcomes linked to CNN output. The goal is to incorporate brilliant algorithms of deep learning into clinical practice to develop a more efficient diagnostic criterion of ailments that affect the chest, early detection and treatment, various treatment plans tailored according to the patient’s needs so as to enhance their quality of life.

Key Words:  DeepLung Diagnosis, Convolutional neural network name as well as Mask CNN for classifying Lung Disease and for interpreting X-ray Images.