Abstract: Breast cancer is one of the most common malignant tumors of women,computer-aided breast tumor detection technology faced on mammogram can help radiologists to detect breast lesions early.Breast tumor detection(BTD) algorithm on fusion of bilateral feature is presented,which aims at the problem that the accuracy of BTD on unilateral feature can be improved.First,preprocess the image and registration the breast contour using the coherent point drift.Then,use transformation matrix obtained from registration to acquire regions of interest(ROIs) of bilateral breast.After that,extract unilateral feature vector of left and right breast and bilateral contrast feature vector in ROIs.Thereby,the fusion feature model is set up,and then the features are selected by genetic algorithm selection.Finally,breast tumor is detected by extreme learning machine based on the selected features.Experimental results show that the proposed BTD algorithm on fusion of bilateral features can improve the accuracy of the detection effectively,compared to the traditional BTD algorithm on unilateral feature.