Particle-cell detecting and tracking in live-cell time-lapse images

Hui Jun Cheng; Jyh Da Wei; Hsin Hsin Peng; Yu Ju Liu

doi:10.1109/ISPAN-FCST-ISCC.2017.58

Particle-cell detecting and tracking in live-cell time-lapse images

Hui Jun Cheng, Jyh Da Wei^*, Hsin Hsin Peng, Yu Ju Liu

^*Corresponding author for this work

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

2 Scopus citations

Abstract

Live-cell time-lapse images generated by biological experiments are useful for observing activities, even for proposing novel hypotheses. By identifying particles and cells as objects from live-cell time-lapse images and then tracking the pathways of particles (or cells) to calculate the measures between the particles and cells, such as the distances, they can be quantized for the relationship of particles and cells. Various tools of particle or cell tracking have been proposed. However, there is no famous tool has been proposed to achieve the above goals. Hence, in order to accomplish the purposes, a particle-cell relation mining method, abbreviate to PCRM, has been proposed here. In the PCRM method, there are four phases: object identification, objects tracking, measures calculation, and relation mining. By using the PCRM method, the relationship between particles and cells has tried to be found in this paper, and the PCRM method is useful for biologists to prove their hypotheses.

Original language	English
Title of host publication	Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	352-356
Number of pages	5
ISBN (Electronic)	9781538608401
DOIs	https://doi.org/10.1109/ISPAN-FCST-ISCC.2017.58
State	Published - 27 11 2017
Event	14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017 - Exeter, Devon, United Kingdom Duration: 21 06 2017 → 23 06 2017

Publication series

Name	Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
Volume	2017-November

Conference

Conference	14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
Country/Territory	United Kingdom
City	Exeter, Devon
Period	21/06/17 → 23/06/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

Live-cell time-lapse image
Measures calculation
Object identification
Particle and cell tracking
Particle-cell distance

Access to Document

10.1109/ISPAN-FCST-ISCC.2017.58

Cite this

Cheng, H. J., Wei, J. D., Peng, H. H., & Liu, Y. J. (2017). Particle-cell detecting and tracking in live-cell time-lapse images. In Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017 (pp. 352-356). (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017; Vol. 2017-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISPAN-FCST-ISCC.2017.58

Cheng, Hui Jun ; Wei, Jyh Da ; Peng, Hsin Hsin et al. / Particle-cell detecting and tracking in live-cell time-lapse images. Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 352-356 (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017).

@inproceedings{497bfdcc41f342788043817ca326fcad,

title = "Particle-cell detecting and tracking in live-cell time-lapse images",

abstract = "Live-cell time-lapse images generated by biological experiments are useful for observing activities, even for proposing novel hypotheses. By identifying particles and cells as objects from live-cell time-lapse images and then tracking the pathways of particles (or cells) to calculate the measures between the particles and cells, such as the distances, they can be quantized for the relationship of particles and cells. Various tools of particle or cell tracking have been proposed. However, there is no famous tool has been proposed to achieve the above goals. Hence, in order to accomplish the purposes, a particle-cell relation mining method, abbreviate to PCRM, has been proposed here. In the PCRM method, there are four phases: object identification, objects tracking, measures calculation, and relation mining. By using the PCRM method, the relationship between particles and cells has tried to be found in this paper, and the PCRM method is useful for biologists to prove their hypotheses.",

keywords = "Live-cell time-lapse image, Measures calculation, Object identification, Particle and cell tracking, Particle-cell distance",

author = "Cheng, {Hui Jun} and Wei, {Jyh Da} and Peng, {Hsin Hsin} and Liu, {Yu Ju}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017 ; Conference date: 21-06-2017 Through 23-06-2017",

year = "2017",

month = nov,

day = "27",

doi = "10.1109/ISPAN-FCST-ISCC.2017.58",

language = "英语",

series = "Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "352--356",

booktitle = "Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017",

address = "美国",

}

Cheng, HJ, Wei, JD , Peng, HH & Liu, YJ 2017, Particle-cell detecting and tracking in live-cell time-lapse images. in Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017, vol. 2017-November, Institute of Electrical and Electronics Engineers Inc., pp. 352-356, 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017, Exeter, Devon, United Kingdom, 21/06/17. https://doi.org/10.1109/ISPAN-FCST-ISCC.2017.58

Particle-cell detecting and tracking in live-cell time-lapse images. / Cheng, Hui Jun; Wei, Jyh Da ; Peng, Hsin Hsin et al.
Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 352-356 (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017; Vol. 2017-November).

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

TY - GEN

T1 - Particle-cell detecting and tracking in live-cell time-lapse images

AU - Cheng, Hui Jun

AU - Wei, Jyh Da

AU - Peng, Hsin Hsin

AU - Liu, Yu Ju

PY - 2017/11/27

Y1 - 2017/11/27

N2 - Live-cell time-lapse images generated by biological experiments are useful for observing activities, even for proposing novel hypotheses. By identifying particles and cells as objects from live-cell time-lapse images and then tracking the pathways of particles (or cells) to calculate the measures between the particles and cells, such as the distances, they can be quantized for the relationship of particles and cells. Various tools of particle or cell tracking have been proposed. However, there is no famous tool has been proposed to achieve the above goals. Hence, in order to accomplish the purposes, a particle-cell relation mining method, abbreviate to PCRM, has been proposed here. In the PCRM method, there are four phases: object identification, objects tracking, measures calculation, and relation mining. By using the PCRM method, the relationship between particles and cells has tried to be found in this paper, and the PCRM method is useful for biologists to prove their hypotheses.

AB - Live-cell time-lapse images generated by biological experiments are useful for observing activities, even for proposing novel hypotheses. By identifying particles and cells as objects from live-cell time-lapse images and then tracking the pathways of particles (or cells) to calculate the measures between the particles and cells, such as the distances, they can be quantized for the relationship of particles and cells. Various tools of particle or cell tracking have been proposed. However, there is no famous tool has been proposed to achieve the above goals. Hence, in order to accomplish the purposes, a particle-cell relation mining method, abbreviate to PCRM, has been proposed here. In the PCRM method, there are four phases: object identification, objects tracking, measures calculation, and relation mining. By using the PCRM method, the relationship between particles and cells has tried to be found in this paper, and the PCRM method is useful for biologists to prove their hypotheses.

KW - Live-cell time-lapse image

KW - Measures calculation

KW - Object identification

KW - Particle and cell tracking

KW - Particle-cell distance

UR - http://www.scopus.com/inward/record.url?scp=85048289121&partnerID=8YFLogxK

U2 - 10.1109/ISPAN-FCST-ISCC.2017.58

DO - 10.1109/ISPAN-FCST-ISCC.2017.58

M3 - 会议稿件

AN - SCOPUS:85048289121

T3 - Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017

SP - 352

EP - 356

BT - Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017

Y2 - 21 June 2017 through 23 June 2017

ER -

Cheng HJ, Wei JD , Peng HH, Liu YJ. Particle-cell detecting and tracking in live-cell time-lapse images. In Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 352-356. (Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017). doi: 10.1109/ISPAN-FCST-ISCC.2017.58

Particle-cell detecting and tracking in live-cell time-lapse images

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this