Breast Tumor Classification from Ultrasound Images Using Fuzzy Inference in MATLAB

Classification of Breast Tumors from Ultrasound Images Using Fuzzy Inference in MATLAB is a method that leverages computational techniques to enhance diagnostic accuracy in medical imaging. Key points include:

• Ultrasound Images: A non-invasive imaging technique used to visualize breast tissue and detect abnormalities.
• Fuzzy Inference System (FIS): A logic-based framework that handles uncertainty and imprecision in medical data.
• MATLAB Implementation: MATLAB is utilized for its robust tools in image processing and fuzzy logic design.
• Classification: Differentiates benign and malignant tumors by analyzing patterns in ultrasound images.
• Applications**: Aids radiologists in providing accurate, fast, and reliable diagnoses.

This approach enhances decision-making and could significantly improve early detection and treatment planning for breast cancer.

Key objectives of this technique include distinguishing between benign and malignant tumors with high accuracy, reducing diagnostic errors, and enabling early detection. This innovative solution bridges the gap between technology and healthcare, significantly improving diagnostic workflows and patient outcomes in oncology. Let me know if you'd like any refinements!