The early diagnosis of diseases is crucial for effective treatment and management. Medical images such as X-rays, MRIs, and CT scans play a vital role in the diagnosis of diseases. However, the analysis of medical images is a complex and time-consuming task that requires the expertise of a trained medical professional. This project aims to develop a disease diagnosis system that can analyze medical images and assist medical professionals in the diagnosis of diseases.
The system will utilize image processing and computer vision techniques, such as feature extraction and object detection, to analyze the images and detect abnormalities. The extracted features will be used to train machine learning algorithms, such as convolutional neural networks (CNNs) & SVmM, to classify the images into different categories based on the detected abnormalities. Tk inter Graphical User Interface(GUI) is used.
svc.pkl is the trained model on SVM kidney_stone_detection_model.h5 is the trained model on CNN
Feel free to contact me.