
AI-powered breast ultrasound classification system using SVM machine learning. Perfect Python final year project classifying tumors as benign, malignant, or normal with 97% accuracy and full source code.
Python 3.10.11 | Flask | Scikit-learn | OpenCV | NumPy | Matplotlib | Seaborn | HTML5 | CSS3 | JavaScript
BreastGuard AI is a powerful AI final year project developed using Python and Machine Learning to classify breast ultrasound images into Benign, Malignant, or Normal categories. This project is designed specifically for students looking for final year projects with source code in Artificial Intelligence and Medical Imaging domains.
The system uses advanced image preprocessing techniques and applies Machine Learning models such as Logistic Regression, K-Nearest Neighbors, and Support Vector Machine (SVM). After model comparison and hyperparameter tuning using GridSearchCV, the optimized SVM model achieves high accuracy in tumor classification.
The uploaded ultrasound image undergoes grayscale conversion, resizing to 128x128 pixels, and flattening into 16,384 features. These features are normalized using StandardScaler before being passed to the trained SVM classifier. The model then predicts the tumor class and returns probability-based confidence scores.
This makes it one of the best AI final year projects for students in Computer Science, Artificial Intelligence, Data Science, and Biomedical Engineering.
If you are searching for a Python final year project with real-world AI implementation, BreastGuard AI is a complete solution. It combines image processing, machine learning, model evaluation, and web deployment in one integrated system.
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