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A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria

机译:由抛物线弧模型驱动的经过验证的主动轮廓线方法用于线粒体的检测和分割

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摘要

Recent studies reveal that mitochondria take substantial responsibility in cellular functions that are closely related to aging diseases caused by degeneration of neurons. These studies emphasize that the membrane and crista morphology of a mitochondrion should receive attention in order to investigate the link between mitochondrial function and its physical structure. Electron microscope tomography (EMT) allows analysis of the inner structures of mitochondria by providing highly detailed visual data from large volumes. Computerized segmentation of mitochondria with minimum manual effort is essential to accelerate the study of mitochondrial structure/function relationships. In this work, we improved and extended our previous attempts to detect and segment mitochondria from transmission electron microcopy (TEM) images. A parabolic arc model was utilized to extract membrane structures. Then, curve energy based active contours were employed to obtain roughly outlined candidate mitochondrial regions. Finally, a validation process was applied to obtain the final segmentation data. 3D extension of the algorithm is also presented in this paper. Our method achieved an average F-score performance of 0.84. Average Dice Similarity Coefficient and boundary error were measured as 0.87 and 14 nm respectively.
机译:最近的研究表明,线粒体在与神经元变性引起的衰老疾病密切相关的细胞功能中起着重要作用。这些研究强调,为了研究线粒体功能与其物理结构之间的联系,应当关注线粒体的膜和cr的形态。电子显微镜断层扫描(EMT)通过提供大量的高度详细的可视数据,可以分析线粒体的内部结构。用最少的人工对线粒体进行计算机分割对于加速线粒体结构/功能关系的研究至关重要。在这项工作中,我们改进和扩展了我们先前从透射电子显微镜(TEM)图像检测和分割线粒体的尝试。利用抛物线弧模型提取膜结构。然后,基于曲线能量的活动轮廓线用于获得大致轮廓的线粒体候选区域。最后,应用验证过程以获得最终的分割数据。本文还介绍了该算法的3D扩展。我们的方法获得了0.84的平均F评分性能。平均骰子相似系数和边界误差分别为0.87和14 nm。

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