Shi Lin, Wang Defeng, Heng Pheng Ann, Wong Tien-Tsin, Chu Winnie C W, Yeung Benson H Y, Cheng Jack C Y
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China.
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):818-25. doi: 10.1007/978-3-540-75759-7_99.
Volumetric layers are often encountered in medical images. Unlike solid structures, volumetric layers are characterized by double and nested bounding surfaces. It is expected that better statistical models can be built by utilizing the surface coupleness rather than simply applying the landmarking method on each of them separately. We propose an approach to optimizing the landmark correspondence on the coupled surfaces by minimizing the description length that incorporates local thickness gradient. The evaluations are performed on a set of 2-D synthetic close coupled contours and a set of real-world open surfaces, the skull vaults. Compared with performing landmarking separately on the coupled surfaces, the proposed method constructs models that have better generalization ability and specificity.
体积层在医学图像中经常出现。与实体结构不同，体积层的特征是具有双重和嵌套的边界表面。预计通过利用表面耦合性而不是简单地在每个表面上单独应用地标法，可以建立更好的统计模型。我们提出了一种方法，通过最小化包含局部厚度梯度的描述长度来优化耦合表面上的地标对应关系。评估是在一组二维合成紧密耦合轮廓和一组真实世界的开放表面（颅顶）上进行的。与在耦合表面上单独进行地标标记相比，所提出的方法构建的模型具有更好的泛化能力和特异性。
