Courtis Patrick, Samani Abbas
Department of Electrical and Computer Engineering, University of Western Ontario.
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):244-51. doi: 10.1007/978-3-540-75759-7_30.
An image registration-based elastography algorithm is presented for assessing the stiffness of tissue regions inside the prostate for the purpose of detecting tumors. A 3D finite-element model of the prostate is built from ultrasound images and used to simulate the deformation of the prostate induced by a TRUS probe. To reconstruct the stiffness of tissues, their Young's moduli are varied using Powell's method so that the mutual information between a simulated and deformed image volume is maximized. The algorithm was validated using a gelatin prostate phantom embedded with a cylindrical inclusion that simulated a tumor. Results from the phantom study showed that the technique could detect the increased stiffness of the simulated tumor with a reasonable accuracy.
提出了一种基于图像配准的弹性成像算法，用于评估前列腺内部组织区域的硬度，以检测肿瘤。从超声图像构建前列腺的三维有限元模型，并用于模拟经直肠超声探头引起的前列腺变形。为了重建组织的硬度，使用鲍威尔方法改变它们的杨氏模量，以使模拟图像体积和变形图像体积之间的互信息最大化。该算法使用嵌入模拟肿瘤的圆柱形内含物的明胶前列腺模型进行了验证。模型研究结果表明，该技术能够以合理的准确度检测出模拟肿瘤的硬度增加。
