果蝇图像分割的b样条水平集

Rim Rahali, Yassine Ben Salem, Noura Dridi, H. Dahman
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引用次数: 1

摘要

由于生物图像的非凸形状、强度不均匀性和细胞聚集性,生物图像的分割是一项具有挑战性的任务。为了解决这些问题,提出了一种基于b样条水平集方法的新算法。将水平集的隐函数建模为用b样条基表示的连续参数函数。它不同于传统水平集的离散公式。本文提出的框架考虑了生物图像的特性。将该算法应用于果蝇图像,并与常规水平集和标记控制分水岭(Marker Controlled Watershed, MCW)进行了比较。结果表明,无论对有噪图像还是无噪图像,该方法都具有良好的DICE系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
B-Spline Level Set For Drosophila Image Segmentation
Segmentation of biological images is a challenging task, due to non convex shapes, intensity inhomogeneity and clustered cells. To address these issues, a new algorithm is proposed based on the B-spline level set method. The implicit function of the level set is modelled as a continuous parametric function represented with the B-spline basis. It is different from the discrete formulation associated with conventional level set. In this paper the proposed framework takes into account properties of biological images. The algorithm is applied to Drosophila images, and compared to conventional level set and Marker Controlled Watershed (MCW). Results show good performance in term of the DICE coefficient, for noisy and noiseless images.
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