Cline H E, Lorensen W E, Kikinis R, Jolesz F
GE Corporate Research and Development Center, Schenectady, NY 12301.
J Comput Assist Tomogr. 1990 Nov-Dec;14(6):1037-45. doi: 10.1097/00004728-199011000-00041.
We describe a three-dimensional (3D) segmentation method that comprises (a) user interactive identification of tissue classes; (b) calculation of a probability distribution for each tissue; (c) creation of a feature map of the most probable tissues; (d) 3D segmentation of the magnetic resonance (MR) data; (e) smoothing of the segmented data; (f) extraction of surfaces of interest with connectivity; (g) generation of surfaces; and (h) rendering of multiple surfaces to plan surgery. Patients with normal head anatomy and with abnormalities such as multiple sclerosis lesions and brain tumors were scanned with a 1.5 T MR system using a two echo contiguous (interleaved), multislice pulse sequence that provides both proton density and T2-weighted contrast. After the user identified the tissues, the 3D data were automatically segmented into background, facial tissue, brain matter, CSF, and lesions. Surfaces of the face, brain, lateral ventricles, tumors, and multiple sclerosis lesions are displayed using color coding and gradient shading. Color improves the visualization of segmented tissues, while gradient shading enhances the perception of depth. Manipulation of the 3D model on a workstation aids surgical planning. Sulci and gyri stand out, thus aiding functional mapping of the brain surface.
我们描述了一种三维（3D）分割方法，该方法包括：（a）用户交互式识别组织类别；（b）计算每个组织的概率分布；（c）创建最可能组织的特征图；（d）对磁共振（MR）数据进行三维分割；（e）对分割后的数据进行平滑处理；（f）提取具有连通性的感兴趣表面；（g）生成表面；以及（h）渲染多个表面以规划手术。使用1.5T MR系统，采用双回波连续（交错）多层脉冲序列对头部解剖结构正常以及患有诸如多发性硬化症病变和脑肿瘤等异常疾病的患者进行扫描，该序列可提供质子密度和T2加权对比度。在用户识别出组织后，三维数据会自动分割为背景、面部组织、脑实质、脑脊液和病变。使用颜色编码和梯度阴影显示面部、大脑、侧脑室、肿瘤和多发性硬化症病变的表面。颜色改善了分割组织的可视化效果，而梯度阴影增强了深度感知。在工作站上对三维模型进行操作有助于手术规划。脑沟和脑回清晰可见，从而有助于大脑表面的功能映射。
