使用时空活动表面和活动轮廓模型进行肌动蛋白丝分割
Actin filament segmentation using spatiotemporal active-surface and active-contour models.
作者信息
Li Hongsheng, Shen Tian, Vavylonis Dimitrios, Huang Xiaolei
机构信息
Department of Computer Science & Engineering, Lehigh University, USA.
出版信息
Med Image Comput Comput Assist Interv. 2010;13(Pt 1):86-94. doi: 10.1007/978-3-642-15705-9_11.
Abstract
We introduce a novel algorithm for actin filament segmentation in a 2D TIRFM image sequence. We treat the 2D time-lapse sequence as a 3D image volume and propose an over-grown active surface model to segment the body of a filament on all slices simultaneously. In order to locate the two ends of the filament on the over-grown surface, a novel 2D spatiotemporal domain is created based on the resulting surface. Two 2D active contour models deform in this domain to locate the two filament ends accurately. Evaluation on TIRFM image sequences with very low SNRs and comparison with a previous method demonstrate the accuracy and robustness of this approach.
摘要
我们介绍了一种用于二维全内反射荧光显微镜（TIRFM）图像序列中肌动蛋白丝分割的新算法。我们将二维时间推移序列视为三维图像体积，并提出一种过度生长的活动表面模型，以同时在所有切片上分割丝状体的主体。为了在过度生长的表面上定位丝状体的两端，基于所得表面创建了一个新颖的二维时空域。两个二维活动轮廓模型在该域中变形，以准确地定位丝状体的两端。在具有非常低信噪比的TIRFM图像序列上进行评估，并与先前的方法进行比较，证明了该方法的准确性和鲁棒性。
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