Sarti Alessandro, Corsi Cristiana, Mazzini Elena, Lamberti Claudio
Department of Electronics, Computer Science and Systems, University of Bologna, Bologna, 1-40136, Italy
IEEE Trans Ultrason Ferroelectr Freq Control. 2005 Jun;52(6):947-60. doi: 10.1109/tuffc.2005.1504017.
This study presents a geometric model and a computational algorithm for segmentation of ultrasound images. A partial differential equation (PDE)-based flow is designed in order to achieve a maximum likelihood segmentation of the target in the scene. The flow is derived as the steepest descent of an energy functional taking into account the density probability distribution of the gray levels of the image as well as smoothness constraints. To model gray level behavior of ultrasound images, the classic Rayleigh probability distribution is considered. The steady state of the flow presents a maximum likelihood segmentation of the target. A finite difference approximation of the flow is derived, and numerical experiments are provided. Results are presented on ultrasound medical images as fetal echography and echocardiography.
本研究提出了一种用于超声图像分割的几何模型和计算算法。设计了一种基于偏微分方程（PDE）的流，以实现场景中目标的最大似然分割。该流是作为能量泛函的最速下降推导出来的，其中考虑了图像灰度级的密度概率分布以及平滑约束。为了对超声图像的灰度行为进行建模，考虑了经典的瑞利概率分布。该流的稳态呈现出目标的最大似然分割。推导了该流的有限差分近似，并提供了数值实验。结果展示在胎儿超声心动图和超声心动描记术等超声医学图像上。
