Poon C S, Braun M
Department of Applied Physics, University of Technology, Sydney, Broadway, NSW, Australia.
Phys Med Biol. 1997 Sep;42(9):1833-41. doi: 10.1088/0031-9155/42/9/013.
Deformable contour models are useful tools for image segmentation. However, many fields depend mainly on local edge-based image features to guide the convergence of the contour. This makes the models sensitive to noise and the initial estimate. Our model incorporates region-based image features to improve its convergence and to reduce its dependence on initial estimation. Computational efficiency is achieved by an optimization strategy, modified from the greedy algorithm of Williams and Shah. The model allows a simultaneous optimization of multiple contours, making it useful for a large variety of segmentation problems.
可变形轮廓模型是图像分割的有用工具。然而，许多领域主要依赖基于局部边缘的图像特征来引导轮廓的收敛。这使得模型对噪声和初始估计敏感。我们的模型纳入了基于区域的图像特征，以提高其收敛性并减少对初始估计的依赖。通过一种从Williams和Shah的贪婪算法修改而来的优化策略实现了计算效率。该模型允许同时优化多个轮廓，使其适用于各种分割问题。
