Author : Keerti.G 1
Date of Publication :5th May 2023
Abstract: Kidney abnormality, which affects millions of individuals worldwide, is one of the key issues in modern society. Computed tomography, a narrow-beam x-ray imaging technology, is utilized to develop cross-sectional slices of the human kidneys to identify various disorders. Computer tomography images have been effectively classified and segmented using different deep-learning algorithms. However, it has proved challenging for healthcare professionals to comprehend the model's precise judgments, leading to a "black box" system. This study suggested a lightweight tailored convolution neural network to identify kidney cysts, stones, and tumours to get around these problems. The suggested CNN model outperformed other cutting-edge techniques and achieved an accuracy of 99.52. The suggested study gives practitioners definitive and clear data with improved outcomes and enhanced interpretative ability. Finally, the flask framework is used to predict web pages.
Reference :