CAJ | 학술논문

乳腺癌是妇女最常见的恶性肿瘤之一，面向乳腺钼靶 X 线图像的计算机辅助肿块检测技术可以帮助影像科医师早期发现乳腺病变。针对于单侧的乳腺肿块检测中准确率有待提升的问题，提出双侧特征融合的乳腺肿块检测算法。首先，进行图像预处理，并利用相干点漂移完成乳腺轮廓配准；然后，利用配准得到的变换矩阵获得双侧乳腺感兴趣区域，再在其中提取左右侧乳腺的单侧特征向量和双侧对比特征向量，从而建立融合的特征模型，并采用遗传选择算法对特征向量进行特征选择；最后利用极限学习机基于选择后的特征进行乳腺肿块检测。实验结果表明，与传统的基于单侧的乳腺肿块检测算法相比，文中算法能有效地提高检测准确率。
유선암시부녀최상견적악성종류지일，면향유선목파 X 선도상적계산궤보조종괴검측기술가이방조영상과의사조기발현유선병변。침대우단측적유선종괴검측중준학솔유대제승적문제，제출쌍측특정융합적유선종괴검측산법。수선，진행도상예처리，병이용상간점표이완성유선륜곽배준；연후，이용배준득도적변환구진획득쌍측유선감흥취구역，재재기중제취좌우측유선적단측특정향량화쌍측대비특정향량，종이건립융합적특정모형，병채용유전선택산법대특정향량진행특정선택；최후이용겁한학습궤기우선택후적특정진행유선종괴검측。실험결과표명，여전통적기우단측적유선종괴검측산법상비，문중산법능유효지제고검측준학솔。
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 de-tection (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 accu-racy of the detection effectively, compared to the traditional BTD algorithm on unilateral feature.