Ultrasound breast tumor grading method based on multi-feature extraction and Linear SVM

The invention discloses an ultrasound breast tumor grading method based on multi-feature extraction and Linear SVM. The method comprises steps that to-be-diagnosed breast ultrasound RF data is inputted; the RF data is converted into an ultrasound B-mode image to obtain the initial suspicious lump area location; the initial suspicious lump area is segmented to obtain a suspicious lump to determinethe boundary of the suspicious lump; a feature value of the segmented suspicious lump is calculated; the calculated feature value is inputted into a classifier, and the suspicious lump area is analyzed. The method is advantaged in that based on the BI-RADS grading standard, the actually acquired breast ultrasound RF data is hierarchically detected, breast tumor ultrasound 3, 4 and 5-level classification is achieved through utilizing the multi-feature extraction method and the linear support vector machine classifier, improvement of accuracy of the doctor's diagnosis is facilitated, the algorithm time and complexity ca