An Automated Workflow for Segmenting Single Adult Cardiac Cells from Large-Volume Serial Block-Face Scanning Electron Microscopy Data
An Automated Workflow for Segmenting Single Adult Cardiac Cells from Large-Volume Serial Block-Face Scanning Electron Microscopy Data
复制标题
从大容量串行块面扫描电子显微镜数据中分割单个成体心肌细胞的自动化工作流程
DOI：
10.1101/242701
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
V. Rajagopal
中科院分区：
文献类型：
--
作者：
A. Hussain;Shouryadipta Ghosh;S. Kalkhoran;D. Hausenloy;E. Hanssen;V. Rajagopal
本文提出了一种新的算法来自动分割肌原纤维，线粒体和细胞核内的单个成年心肌细胞，是一个大的连续块面扫描电子显微镜（SBF-SEM）数据集的一部分。该算法只需要一组手动绘制的轮廓，这些轮廓以常规切片间隔（例如，每隔50个切片）粗略地划分细胞边界。与手动分割相比，该算法以97%的准确度正确地对单个细胞内的像素进行分类。一个完整的细胞和两个细胞的部分体积被分割。这些细胞内的分割分析表明，肌原纤维和线粒体平均分别占47.5%和51.6%，而细胞核占细胞的0.7%，其中整个体积被捕获在SBF-SEM数据集中。心肌细胞核周围及分支点线粒体聚集增多。分割还显示在肌膜下区域中线粒体的高面积分数（高达2D图像切片的70%），而在肌原纤维间空间中接近50%。我们最后证明，我们的分割可以变成三维有限元网格的心脏细胞计算生理学研究。我们在www.github.com/CellSMB/sbfsem-cardiac-cell-segmenter/上提供了我们的大型数据集和算法的MATLAB实现供研究使用。我们预计，这个及时的工具将用于心脏计算和实验生理学家谁研究心脏超微结构及其在心脏功能中的作用。
This paper presents a new algorithm to automatically segment the myofibrils, mitochondria and nuclei within single adult cardiac cells that are part of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The algorithm only requires a set of manually drawn contours that roughly demarcate the cell boundary at routine slice intervals (every 50th, for example). The algorithm correctly classified pixels within the single cell with 97% accuracy when compared to manual segmentations. One entire cell and the partial volumes of two cells were segmented. Analysis of segmentations within these cells showed that myofibrils and mitochondria occupied 47.5% and 51.6% on average respectively, while the nuclei occupy 0.7% of the cell for which the entire volume was captured in the SBF-SEM dataset. Mitochondria clustering increased at the periphery of the nucleus region and branching points of the cardiac cell. The segmentations also showed high area fraction of mitochondria (up to 70% of the 2D image slice) in the sub-sarcolemmal region, whilst it was closer to 50% in the intermyofibrillar space. We finally demonstrate that our segmentations can be turned into 3D finite element meshes for cardiac cell computational physiology studies. We offer our large dataset and MATLAB implementation of the algorithm for research use at www.github.com/CellSMB/sbfsem-cardiac-cell-segmenter/. We anticipate that this timely tool will be of use to cardiac computational and experimental physiologists alike who study cardiac ultrastructure and its role in heart function.
影响因子：
8.8
作者：
Glancy B;Hartnell LM;Combs CA;Femnou A;Sun J;Murphy E;Subramaniam S;Balaban RS
通讯作者：
Balaban RS