Published Paper Details:

Tumors, cysts, and stones of the kidneys are among the serious problems in public health. It is critical to diagnose them early and accurately to achieve successful treatment. The current work aims to produce a web-based application for analyzing kidney CT scans by using deep learning techniques, based on a method known as CNN, in which the classification between Tumor, Cyst, Stone, or Normal occurs. The system makes further classification of renal cell images into predefined five classes in order to identify the malignancy level when a tumor is detected. The CNN model is trained based on a dataset 1 created from kidney CT scans sourced from Kaggle. The system designed by this approach offers an upload interface for images and provides diagnostic results in a very user-friendly manner. This project helps in diagnosing earlier and aids doctors to devise treatment planning which improves the management of kidney health care and the care of patients.