首页> 外文会议>International conference on medical image computing and computer-assisted intervention;MICCAI 2010 >Actin Filament Segmentation Using Spatiotemporal Active-Surface and Active-Contour Models
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Actin Filament Segmentation Using Spatiotemporal Active-Surface and Active-Contour Models

机译:使用时空活动曲面和活动轮廓模型进行肌动蛋白丝分割

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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.
机译:我们介绍了一种二维TIRFM图像序列中肌动蛋白丝分割的新算法。我们将2D延时序列视为3D图像体积,并提出了一个过度生长的活动表面模型,以同时在所有切片上分割细丝的主体。为了将长丝的两端定位在过度生长的表面上,基于生成的表面创建了一个新颖的2D时空域。两个2D活动轮廓模型在该区域变形,以精确定位两个细丝末端。对具有极低SNR的TIRFM图像序列进行评估并与以前的方法进行比较,证明了该方法的准确性和鲁棒性。

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