Enhancing the morphological segmentation of microscopic fossils through Localized Topology-Aware Edge Detection

Enhancing the morphological segmentation of microscopic fossils through Localized Topology-Aware Edge Detection
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DOI:
10.1007/s10514-020-09950-9
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发表时间:
2020-11
期刊:
影响因子:
3.5
通讯作者:
Qian Ge;Turner Richmond;Boxuan Zhong;T. Marchitto;E. Lobaton
Qian Ge;Turner Richmond;Boxuan Zhong;T. Marchitto;E. Lobaton
中科院分区:
计算机科学3区
文献类型:
--
作者:
Qian Ge;Turner Richmond;Boxuan Zhong;T. Marchitto;E. Lobaton

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被称为有孔虫的化石单细胞海洋生物被广泛用于海洋学研究。物种识别是分析海洋样品时最常见的任务之一。物种鉴定的主要标准之一是它们的形态。有孔虫图像的自动分割将有助于识别任务以及其他形态学研究。我们把这个问题作为一个边缘检测任务,捕捉正确的拓扑结构是必不可少的。由于软边缘甚至未闭合段的存在,现有技术在捕获正确的边缘结构方面存在问题。标准的基于像素的损失函数也对边缘的小变形和移位敏感,从而比实际结构更严重地惩罚位置。因此,我们提出了一个同源性为基础的检测器的局部结构差异的两个边缘地图与一个可容忍的变形。该检测器被用作训练和设计数据驱动方法的新标准,这些方法专注于增强这些结构差异。我们的方法表现出显着的改善形态分割有孔虫时,考虑到基于区域和基于拓扑的指标。海洋研究人员对结果质量进行的人类排名也支持这些发现。
Fossil single-celled marine organisms known as foraminifera are widely used in oceanographic research. The identification of species is one of the most common tasks when analyzing ocean samples. One of the primary criteria for species identification is their morphology. Automatic segmentation of images of foraminifera would aid on the identification task as well as on other morphological studies. We pose this problem as an edge detection task for which capturing the correct topological structure is essential. Due to the presence of soft edges and even unclosed segments, state-of-the-art techniques have problems capturing the correct edge structure. Standard pixel-based loss functions are also sensitive to small deformations and shifts of the edges penalizing location more heavily than actual structure. Hence, we propose a homology-based detector of local structural difference between two edge maps with a tolerable deformation. This detector is employed as a new criterion for the training and design of data-driven approaches that focus on enhancing these structural differences. Our approaches demonstrate significant improvement on morphological segmentation of foraminifera when considering region-based and topology-based metrics. Human ranking of the quality of the results by marine researchers also supports these findings.