Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan.
Department of Computer Science, Tunghai University, Taichung, Taiwan.
J Digit Imaging. 2019 Oct;32(5):713-727. doi: 10.1007/s10278-019-00190-7.
The shape and contour of the lesion are shown to be effective features for physicians to identify breast tumor as benign or malignant. The region of the lesion is usually manually created by the physician according to their clinical experience; therefore, contouring tumors on breast magnetic resonance imaging (MRI) is difficult and time-consuming. For this purpose, an automatic contouring method for breast tumors was developed for less burden in the analysis and to decrease the observed bias to help in making decisions clinically. In this study, a multiview segmentation method for detecting and contouring breast tumors in MRI was represented. The preprocessing of the proposed method reduces any amount of noises but preserves the shape and contrast of the breast tumor. The two-dimensional (2D) level-set segmentation method extracts contours of breast tumors from the transverse, coronal, and sagittal planes. The obtained contours are further utilized to generate appropriate three-dimensional (3D) contours. Twenty breast tumor cases were evaluated and the simulation results show that the proposed contouring method was an efficient method for delineating 3D contours of breast tumors in MRI.
病变的形状和轮廓被证明是医生识别乳腺肿瘤良性或恶性的有效特征。病变区域通常是根据医生的临床经验手动创建的;因此,对乳腺磁共振成像 (MRI) 中的肿瘤进行轮廓绘制既困难又耗时。为此,开发了一种用于乳腺肿瘤的自动轮廓绘制方法,以减轻分析负担并减少观察到的偏差,从而有助于临床决策。在这项研究中,提出了一种用于在 MRI 中检测和勾勒乳腺肿瘤的多视图分割方法。该方法的预处理减少了任何数量的噪声,但保留了乳腺肿瘤的形状和对比度。二维 (2D) 水平集分割方法从横断、冠状和矢状平面提取乳腺肿瘤的轮廓。获得的轮廓进一步用于生成适当的三维 (3D) 轮廓。对 20 例乳腺肿瘤病例进行了评估,模拟结果表明,所提出的轮廓绘制方法是一种有效的方法,可用于描绘 MRI 中乳腺肿瘤的 3D 轮廓。