Segmentation of 3D images of plant tissues at multiple scales using the level set method.
Segmentation of 3D images of plant tissues at multiple scales using the level set method.
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DOI：
10.1186/s13007-017-0264-5
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发表时间：
2017
期刊：
影响因子：
5.1
通讯作者：
Das P
中科院分区：
文献类型：
--
作者：
Kiss A;Moreau T;Mirabet V;Calugaru CI;Boudaoud A;Das P
近年来，发育生物学在发育过程中细胞特性的量化方面取得了巨大进步。这需要对组织进行成像和分割，以生成易于分析的计算机化版本。在这种情况下，主要的技术挑战之一仍然是细胞轮廓的忠实检测，这主要是由于整个组织的图像强度的变化。分水岭分割方法特别容易受到这些变化的影响，特别是由于组织外表面的错误检测而产生多个错误。我们使用水平集方法（LSM）以不同的方式提高分水岭分割的准确性。首先，我们检测组织的外表面，减少成像过程中表面低对比度和可变对比度的影响。其次，我们演示了基于图像的二阶导数的水平集的新边缘函数，以分割单个细胞。最后，我们还表明 LSM 可用于分割组织内的细胞核。当与基于 LSM 的表面检测步骤相结合时，外细胞层的分水岭分割得到了明显改善。该工具还可用于改进细胞尺度的分水岭分割，以及分割组织内的细胞核。改进的分割提高了分析质量，并且我们的算法检测到的表面可用于计算局部曲率或适用于其他用途，例如数学模拟。本文的在线版本 (10.1186/s13007-017-0264-5) 包含补充材料，可供授权用户使用。
Developmental biology has made great strides in recent years towards the quantification of cellular properties during development. This requires tissues to be imaged and segmented to generate computerised versions that can be easily analysed. In this context, one of the principal technical challenges remains the faithful detection of cellular contours, principally due to variations in image intensity throughout the tissue. Watershed segmentation methods are especially vulnerable to these variations, generating multiple errors due notably to the incorrect detection of the outer surface of the tissue. We use the level set method (LSM) to improve the accuracy of the watershed segmentation in different ways. First, we detect the outer surface of the tissue, reducing the impact of low and variable contrast at the surface during imaging. Second, we demonstrate a new edge function for a level set, based on second order derivatives of the image, to segment individual cells. Finally, we also show that the LSM can be used to segment nuclei within the tissue. The watershed segmentation of the outer cell layer is demonstrably improved when coupled with the LSM-based surface detection step. The tool can also be used to improve watershed segmentation at cell-scale, as well as to segment nuclei within a tissue. The improved segmentation increases the quality of analysis, and the surface detected by our algorithm may be used to calculate local curvature or adapted for other uses, such as mathematical simulations. The online version of this article (10.1186/s13007-017-0264-5) contains supplementary material, which is available to authorized users.
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影响因子：
7.7
作者：
Barbier de Reuille P;Routier-Kierzkowska AL;Kierzkowski D;Bassel GW;Schüpbach T;Tauriello G;Bajpai N;Strauss S;Weber A;Kiss A;Burian A;Hofhuis H;Sapala A;Lipowczan M;Heimlicher MB;Robinson S;Bayer EM;Basler K;Koumoutsakos P;Roeder AH;Aegerter-Wilmsen T;Nakayama N;Tsiantis M;Hay A;Kwiatkowska D;Xenarios I;Kuhlemeier C;Smith RS
通讯作者：
Smith RS
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影响因子：
5.1
作者：
Mairhofer S;Zappala S;Tracy S;Sturrock C;Bennett MJ;Mooney SJ;Pridmore TP
通讯作者：
Pridmore TP
影响因子：
3.7
作者：
Chopin J;Laga H;Huang CY;Heuer S;Miklavcic SJ
通讯作者：
Miklavcic SJ
影响因子：
10.6
作者：
Li, Chunming;Xu, Chenyang;Fox, Martin D.
通讯作者：
Fox, Martin D.
影响因子：
16.6
作者：
Faure E;Savy T;Rizzi B;Melani C;Stašová O;Fabrèges D;Špir R;Hammons M;Čúnderlík R;Recher G;Lombardot B;Duloquin L;Colin I;Kollár J;Desnoulez S;Affaticati P;Maury B;Boyreau A;Nief JY;Calvat P;Vernier P;Frain M;Lutfalla G;Kergosien Y;Suret P;Remešíková M;Doursat R;Sarti A;Mikula K;Peyriéras N;Bourgine P
通讯作者：
Bourgine P