用自适应阈值和统计特征提取对乳腺癌图像进行分类附matlab代码.zip

# Breast-Cancer-Detection **Title: Breast Cancer Image Classification Using Adaptive Thresholding** **Description:** This repository contains the implementation of an innovative approach to classify breast cancer images, leveraging the power of MATLAB for image processing and statistical feature extraction. The project showcases the use of adaptive thresholding techniques to preprocess the images, enhancing their features for more accurate classification. Key components of this repository include: - **Adaptive Thresholding Implementation:** MATLAB scripts demonstrating the adaptive thresholding process applied to medical images to highlight pertinent features. - **Statistical Feature Extraction:** Code and methodologies for extracting statistical features from the thresholded images, forming the basis for our classification model. - **Classification Algorithms:** A collection of machine learning algorithms employed to classify the images into benign or malignant categories, based on the extracted features. - **Performance Evaluation:** Results and analysis of the classification models, including accuracy, precision, and recall metrics to evaluate the effectiveness of the approach. This project aims to contribute to the medical imaging field by providing a reliable and efficient method for breast cancer detection, utilizing advanced image processing and machine learning techniques.