Development of Medical Image Analytics by Deep Learning Model for Prediction and Classification of CT Image Diseases

The CT images of Lung illnesses or diseases that damage the lungs and weaken respiratory system. cancer is one topmost causes death in humans around world. Humans have a better chance surviving if they are detected early. average survival rate persons with lung increases from 14 to 49 percent disease While computed tomography (CT) significantly more effective than X-ray, complete diagnosis requires combination imaging techniques complement each other. But, because there multiple phases develop into different types tumors varying sizes risks, finding does not predict risk cancer. A deep neural network constructed tested for detecting images. This research work analyses tumor such as large cell carcinoma, normal, squamous adenocarcinoma. Also, predicted help computer vision methods Residual (ResNet), Convolutional (CNN). Finally, results all compared various parameters were calculated. Thus, proposed method (ResNet) gives an optimal solution on comparison respect parameters.