DEEP LEARNING BASED KIDNEY DISEASE CLASSIFICATION SYSTEM

DEEP LEARNING BASED KIDNEY DISEASE CLASSIFICATION SYSTEM

Manjunath R1, Dr. Geetha M2

[1] Student, Department of MCA, BIET, Davangere

[2] Associate Professor, Department of MCA, BIET, Davangere

ABSTRACT

Kidney disease is a significant global health issue that requires timely and accurate diagnosis to improve patient outcomes. This project presents a deep learning-based kidney classification system designed to assist in the early detection and classification of various kidney conditions using medical imaging data. The proposed system leverages advanced convolutional neural networks (CNNs) to analyze and classify kidney ultrasound and MRI images, distinguishing between healthy kidneys and those affected by diseases such as kidney stones, cysts, and tumors. This methodology enhances the model's ability to learn intricate patterns and features associated with different kidney conditions, ensuring high classification accuracy and robustness.

Keywords: Deep Learning, Kidney Classification, Medical Imaging, Convolutional Neural Networks (CNNs)