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

doi:10.5194/jm-40-163-2021

IVPP-IR > 中科院古脊椎所（2000年以后）

	Semantic segmentation of vertebrate microfossils from computed tomography data using a deep learning approach
	Hou, Yemao 1,2,3; Canul-Ku, Mario 4; Cui, Xindong 2,3,5; Hasimoto-Beltran, Rogelio 4; Zhu, Min2,3,5
	2021-10-22
发表期刊	JOURNAL OF MICROPALAEONTOLOGY
ISSN	0262-821X
卷号	40 期号:2 页码:163-173
摘要	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.
DOI	10.5194/jm-40-163-2021
关键词[WOS]	VIRTUAL WORLD ; IMAGE
收录类别	SCI
语种	英语
资助项目	Chinese Academy of Sciences[XDB26000000] ; Chinese Academy of Sciences[XDA19050102] ; Chinese Academy of Sciences[QYZDJ-SSW-DQC002] ; National Natural Science Foundation of China[42130209]
WOS研究方向	Paleontology
WOS类目	Paleontology
WOS记录号	WOS:000710814100001
出版者	COPERNICUS GESELLSCHAFT MBH
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.205/handle/311034/19053
专题	中科院古脊椎所（2000年以后）
通讯作者	Hasimoto-Beltran, Rogelio; Zhu, Min
作者单位	1.Xidian Univ, Sch Life Sci & Technol, Xian 710071, Peoples R China 2.Chinese Acad Sci, Key Lab Vertebrate Evolut & Human Origins, Inst Vertebrate Paleontol & Paleoanthropol, Beijing 100044, Peoples R China 3.CAS Ctr Excellence Life & Paleoenvironm, Beijing 100044, Peoples R China 4.Ctr Invest Matemat CIMAT, Guanajuato 36023, Mexico 5.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Hou, Yemao,Canul-Ku, Mario,Cui, Xindong,et al. Semantic segmentation of vertebrate microfossils from computed tomography data using a deep learning approach[J]. JOURNAL OF MICROPALAEONTOLOGY,2021,40(2):163-173.
APA	Hou, Yemao,Canul-Ku, Mario,Cui, Xindong,Hasimoto-Beltran, Rogelio,&Zhu, Min.(2021).Semantic segmentation of vertebrate microfossils from computed tomography data using a deep learning approach.JOURNAL OF MICROPALAEONTOLOGY,40(2),163-173.
MLA	Hou, Yemao,et al."Semantic segmentation of vertebrate microfossils from computed tomography data using a deep learning approach".JOURNAL OF MICROPALAEONTOLOGY 40.2(2021):163-173.

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