Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network

Xin Wang; Tingfa Xu; Jizhou Zhang; Shushan Wang; Yizhou Zhang; Yiwen Chen; Jinhua Zhang

doi:10.1007/978-981-15-8411-4_92

Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network

Xin Wang, Tingfa Xu^*, Jizhou Zhang, Shushan Wang, Yizhou Zhang, Yiwen Chen, Jinhua Zhang

^*Corresponding author for this work

School of Optics and Photonics

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In bone marrow examination, the number of bone marrow cells is an essential parameter to judge the degree of myeloproliferative. In this paper, we propose a new bone marrow cell counting method based on Fourier ptychographic microscopy and convolutional neural network. We use Fourier ptychographic microscopy technology to obtain the intensity and phase images of bone marrow cells at first. Then, we combine the intensity and the phase image correspondingly to obtain a dual-channel image. We use the convolutional neural network to extract the characteristics of bone marrow cells in the dual-channel image, which can generate a density map. The number of bone marrow cells is realized by integrating the density map. The experimental results show that both the mean absolute error (MAE = 0.66) and mean square error (MSE = 0.67) of our method are lower than those existing methods.

Original language	English
Title of host publication	Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems
Editors	Qilian Liang, Wei Wang, Xin Liu, Zhenyu Na, Xiaoxia Li, Baoju Zhang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	687-693
Number of pages	7
ISBN (Print)	9789811584107
DOIs	https://doi.org/10.1007/978-981-15-8411-4_92
Publication status	Published - 2021
Event	9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020 - Changbaishan, China Duration: 4 Jul 2020 → 5 Jul 2020

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	654 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020
Country/Territory	China
City	Changbaishan
Period	4/07/20 → 5/07/20

Keywords

Bone marrow cells
Convolutional neural network
Counting
Fourier ptychographic microscopy

Access to Document

10.1007/978-981-15-8411-4_92

Cite this

Wang, X., Xu, T., Zhang, J., Wang, S., Zhang, Y., Chen, Y., & Zhang, J. (2021). Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network. In Q. Liang, W. Wang, X. Liu, Z. Na, X. Li, & B. Zhang (Eds.), Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems (pp. 687-693). (Lecture Notes in Electrical Engineering; Vol. 654 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-15-8411-4_92

Wang, Xin ; Xu, Tingfa ; Zhang, Jizhou et al. / Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network. Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems. editor / Qilian Liang ; Wei Wang ; Xin Liu ; Zhenyu Na ; Xiaoxia Li ; Baoju Zhang. Springer Science and Business Media Deutschland GmbH, 2021. pp. 687-693 (Lecture Notes in Electrical Engineering).

@inproceedings{82f762e0bbb54e95b365d900825d6110,

title = "Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network",

abstract = "In bone marrow examination, the number of bone marrow cells is an essential parameter to judge the degree of myeloproliferative. In this paper, we propose a new bone marrow cell counting method based on Fourier ptychographic microscopy and convolutional neural network. We use Fourier ptychographic microscopy technology to obtain the intensity and phase images of bone marrow cells at first. Then, we combine the intensity and the phase image correspondingly to obtain a dual-channel image. We use the convolutional neural network to extract the characteristics of bone marrow cells in the dual-channel image, which can generate a density map. The number of bone marrow cells is realized by integrating the density map. The experimental results show that both the mean absolute error (MAE = 0.66) and mean square error (MSE = 0.67) of our method are lower than those existing methods.",

keywords = "Bone marrow cells, Convolutional neural network, Counting, Fourier ptychographic microscopy",

author = "Xin Wang and Tingfa Xu and Jizhou Zhang and Shushan Wang and Yizhou Zhang and Yiwen Chen and Jinhua Zhang",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020 ; Conference date: 04-07-2020 Through 05-07-2020",

year = "2021",

doi = "10.1007/978-981-15-8411-4_92",

language = "English",

isbn = "9789811584107",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "687--693",

editor = "Qilian Liang and Wei Wang and Xin Liu and Zhenyu Na and Xiaoxia Li and Baoju Zhang",

booktitle = "Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems",

address = "Germany",

}

Wang, X, Xu, T, Zhang, J, Wang, S, Zhang, Y, Chen, Y & Zhang, J 2021, Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network. in Q Liang, W Wang, X Liu, Z Na, X Li & B Zhang (eds), Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol. 654 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 687-693, 9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020, Changbaishan, China, 4/07/20. https://doi.org/10.1007/978-981-15-8411-4_92

Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network. / Wang, Xin; Xu, Tingfa; Zhang, Jizhou et al.
Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems. ed. / Qilian Liang; Wei Wang; Xin Liu; Zhenyu Na; Xiaoxia Li; Baoju Zhang. Springer Science and Business Media Deutschland GmbH, 2021. p. 687-693 (Lecture Notes in Electrical Engineering; Vol. 654 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network

AU - Wang, Xin

AU - Xu, Tingfa

AU - Zhang, Jizhou

AU - Wang, Shushan

AU - Zhang, Yizhou

AU - Chen, Yiwen

AU - Zhang, Jinhua

PY - 2021

Y1 - 2021

N2 - In bone marrow examination, the number of bone marrow cells is an essential parameter to judge the degree of myeloproliferative. In this paper, we propose a new bone marrow cell counting method based on Fourier ptychographic microscopy and convolutional neural network. We use Fourier ptychographic microscopy technology to obtain the intensity and phase images of bone marrow cells at first. Then, we combine the intensity and the phase image correspondingly to obtain a dual-channel image. We use the convolutional neural network to extract the characteristics of bone marrow cells in the dual-channel image, which can generate a density map. The number of bone marrow cells is realized by integrating the density map. The experimental results show that both the mean absolute error (MAE = 0.66) and mean square error (MSE = 0.67) of our method are lower than those existing methods.

AB - In bone marrow examination, the number of bone marrow cells is an essential parameter to judge the degree of myeloproliferative. In this paper, we propose a new bone marrow cell counting method based on Fourier ptychographic microscopy and convolutional neural network. We use Fourier ptychographic microscopy technology to obtain the intensity and phase images of bone marrow cells at first. Then, we combine the intensity and the phase image correspondingly to obtain a dual-channel image. We use the convolutional neural network to extract the characteristics of bone marrow cells in the dual-channel image, which can generate a density map. The number of bone marrow cells is realized by integrating the density map. The experimental results show that both the mean absolute error (MAE = 0.66) and mean square error (MSE = 0.67) of our method are lower than those existing methods.

KW - Bone marrow cells

KW - Convolutional neural network

KW - Counting

KW - Fourier ptychographic microscopy

UR - http://www.scopus.com/inward/record.url?scp=85111365979&partnerID=8YFLogxK

U2 - 10.1007/978-981-15-8411-4_92

DO - 10.1007/978-981-15-8411-4_92

M3 - Conference contribution

AN - SCOPUS:85111365979

SN - 9789811584107

T3 - Lecture Notes in Electrical Engineering

SP - 687

EP - 693

BT - Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems

A2 - Liang, Qilian

A2 - Wang, Wei

A2 - Liu, Xin

A2 - Na, Zhenyu

A2 - Li, Xiaoxia

A2 - Zhang, Baoju

PB - Springer Science and Business Media Deutschland GmbH

T2 - 9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020

Y2 - 4 July 2020 through 5 July 2020

ER -

Wang X, Xu T, Zhang J, Wang S, Zhang Y, Chen Y et al. Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network. In Liang Q, Wang W, Liu X, Na Z, Li X, Zhang B, editors, Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems. Springer Science and Business Media Deutschland GmbH. 2021. p. 687-693. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-15-8411-4_92

Bone Marrow Cell Counting Method Based on Fourier Ptychographic Microscopy and Convolutional Neural Network

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this