Enhancing the morphological segmentation of microscopic fossils through Localized Topology-Aware Edge Detection
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Enhancing the morphological segmentation of microscopic fossils through Localized Topology-Aware Edge Detection Qian Ge1 · Turner Richmond1 · Boxuan Zhong1 · Thomas M. Marchitto2,3 · Edgar J. Lobaton1 Received: 13 January 2020 / Accepted: 29 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract 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. Keywords Edge detection · Topological structure · Morphological segmentation
1 Introduction Foraminifera, also known as forams, are ubiquitous ocean dwelling amoeboid organisms whose shells (typically less than 1 mm in diameter) are widely used in oceanographic This work was supported by US National Science Foundation Grants OCE-1637023, OCE-1637039, OCE-1829970 and OCE-1829930. This is one of the several papers published in Autonomous Robots comprising the Special Issue on Topological Methods in Robotics. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10514-020-09950-9) contains supplementary material, which is available to authorized users.
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Edgar J. Lobaton [email protected]
1
Department of Electrical and Computer Engineering, North Carolina State University, Box 7911, Raleigh, NC 27695, USA
2
Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA
3
Department of Geological Sciences, University of Colorado, Boulder, CO 80309, USA
and geoscience research. They are common in many modern and ancient marine environments, and as such have become invaluable tools for petroleum exploration (Tipsword 1962), paleoecology (Berggren 1992), biostratigraphy (Kennett and Srinivasan 1983), paleobiogeography (Berggren 1972), and paleoclimatology (Rohling and Cooke 1999). One of the mo
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