Semantic segmentation of vertebrate microfossils from computed tomography data using a deep learning approach

Yemao Hou,Mario Canul-Ku,Min Zhu,Rogelio Hasimoto-Beltran,Xindong Cui

doi:10.5194/jm-40-163-2021

Abstract

Abstract. Vertebrate microfossils have broad applications in evolutionary biology and stratigraphy research areas such as the evolution of hard tissues and stratigraphic correlation. Classification is one of the basic tasks of vertebrate microfossil studies. With the development of techniques for virtual paleontology, vertebrate microfossils can be classified efficiently based on 3D volumes. The semantic segmentation of different fossils and their classes from CT data is a crucial step in the reconstruction of their 3D volumes. Traditional segmentation methods adopt thresholding combined with manual labeling, which is a time-consuming process. Our study proposes a deep-learning-based (DL-based) semantic segmentation method for vertebrate microfossils from CT data. To assess the performance of the method, we conducted extensive experiments on nearly 500 fish microfossils. The results show that the intersection over union (IoU) performance metric arrived at least 94.39 %, meeting the semantic segmentation requirements of paleontologists. We expect that the DL-based method could also be applied to other fossils from CT data with good performance.

Highlights

Paleozoic vertebrate microfossils provide important evidence for biostratigraphy, paleobiodiversity, and paleogeography (Zhao and Zhu, 2014; Zhao et al, 2018; Ogg et al, 2016; Märss et al, 1995; Žigaiteet al., 2011; Wang, 2006), as well as oil and gas exploration (Hackley et al, 2017; Funkhouser and Evitt, 1959)
As one subset of vertebrate microfossils, fish microfossils significantly contribute to the study of early vertebrate evolution (Janvier, 1996; Cui et al, 2020; Wang, 1984; Chen et al, 2016; Botella et al, 2007; Cui et al, 2021)
The intersection over union (IoU) score is defined as the size of the intersection divided by the size of the union of the sample sets and computed as follows: TP

Summary

Introduction

Paleozoic vertebrate microfossils provide important evidence for biostratigraphy, paleobiodiversity, and paleogeography (Zhao and Zhu, 2014; Zhao et al, 2018; Ogg et al, 2016; Märss et al, 1995; Žigaiteet al., 2011; Wang, 2006), as well as oil and gas exploration (Hackley et al, 2017; Funkhouser and Evitt, 1959). As one subset of vertebrate microfossils, fish microfossils significantly contribute to the study of early vertebrate evolution (Janvier, 1996; Cui et al, 2020; Wang, 1984; Chen et al, 2016; Botella et al, 2007; Cui et al, 2021). Digital techniques have been used to classify fish microfossils in 3D volumes (Cui et al, 2020, 2021). Semantic image segmentation is a crucial step in the reconstruction of 3D volumes. This task requires a lot of time in addition to expertise in paleontology

Results

Discussion

Conclusion