Computational image modeling for characterization and analysis of intracellular cargo transport

Kuan Chieh Chen; Minhua Qiu; Jelena Kovacevic; Ge Yang

doi:10.1007/978-3-319-09994-1_30

Computational image modeling for characterization and analysis of intracellular cargo transport

Kuan Chieh Chen, Minhua Qiu, Jelena Kovacevic, Ge Yang

Electrical and Computer Engineering

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

Abstract

Active intracellular cargo transport is essential to survival and function of eukaryotic cells. How this process is controlled spatially and temporally so that the right cargo is delivered to the right destination at the right time remains poorly understood. To address this question, it is essential to characterize and analyze the molecular machinery and spatiotemporal behavior of intracellular transport. To this end, we developed related computational image models. Specifically, to study the molecular machinery of intracellular transport, we developed anisotropic spatial density kernels for reconstruction and segmentation of related super-resolution STORM (stochastic optical reconstruction microscopy) images. To study the spatiotemporal behavior of intracellular transport, we developed hidden Markov models and principal component analysis for representation and analysis of movement of individual transported cargoes. We validated and benchmarked the image models using simulated and actual experimental images. The models and related computational analysis methods developed in this study are general and can be used for studying molecular machinery and spatiotemporal dynamics of other cellular processes.

Original language	English (US)
Title of host publication	Computational Modeling of Objects Presented in Images
Subtitle of host publication	Fundamentals, Methods, and Applications - 4th International Conference, CompIMAGE 2014, Proceedings
Publisher	Springer Verlag
Pages	292-303
Number of pages	12
ISBN (Print)	9783319099934
DOIs	https://doi.org/10.1007/978-3-319-09994-1_30
State	Published - 2014
Event	4th International Conference on Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications, CompIMAGE 2014 - Pittsburgh, PA, United States Duration: Sep 3 2014 → Sep 5 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8641 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th International Conference on Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications, CompIMAGE 2014
Country/Territory	United States
City	Pittsburgh, PA
Period	9/3/14 → 9/5/14

Keywords

STORM imaging
hidden Markov model
image modeling
intracellular transport
principal component analysis
spatial density estimation
spatiotemporal dynamics
super-resolution imaging

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-09994-1_30

Cite this

Chen, K. C., Qiu, M., Kovacevic, J., & Yang, G. (2014). Computational image modeling for characterization and analysis of intracellular cargo transport. In Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications - 4th International Conference, CompIMAGE 2014, Proceedings (pp. 292-303). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8641 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-09994-1_30

Computational image modeling for characterization and analysis of intracellular cargo transport. / Chen, Kuan Chieh; Qiu, Minhua; Kovacevic, Jelena et al.
Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications - 4th International Conference, CompIMAGE 2014, Proceedings. Springer Verlag, 2014. p. 292-303 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8641 LNCS).

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

Chen, KC, Qiu, M, Kovacevic, J & Yang, G 2014, Computational image modeling for characterization and analysis of intracellular cargo transport. in Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications - 4th International Conference, CompIMAGE 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8641 LNCS, Springer Verlag, pp. 292-303, 4th International Conference on Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications, CompIMAGE 2014, Pittsburgh, PA, United States, 9/3/14. https://doi.org/10.1007/978-3-319-09994-1_30

Chen KC, Qiu M, Kovacevic J, Yang G. Computational image modeling for characterization and analysis of intracellular cargo transport. In Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications - 4th International Conference, CompIMAGE 2014, Proceedings. Springer Verlag. 2014. p. 292-303. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-09994-1_30

Chen, Kuan Chieh ; Qiu, Minhua ; Kovacevic, Jelena et al. / Computational image modeling for characterization and analysis of intracellular cargo transport. Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications - 4th International Conference, CompIMAGE 2014, Proceedings. Springer Verlag, 2014. pp. 292-303 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{10303461f1d54d01807dfe01cb480e98,

title = "Computational image modeling for characterization and analysis of intracellular cargo transport",

abstract = "Active intracellular cargo transport is essential to survival and function of eukaryotic cells. How this process is controlled spatially and temporally so that the right cargo is delivered to the right destination at the right time remains poorly understood. To address this question, it is essential to characterize and analyze the molecular machinery and spatiotemporal behavior of intracellular transport. To this end, we developed related computational image models. Specifically, to study the molecular machinery of intracellular transport, we developed anisotropic spatial density kernels for reconstruction and segmentation of related super-resolution STORM (stochastic optical reconstruction microscopy) images. To study the spatiotemporal behavior of intracellular transport, we developed hidden Markov models and principal component analysis for representation and analysis of movement of individual transported cargoes. We validated and benchmarked the image models using simulated and actual experimental images. The models and related computational analysis methods developed in this study are general and can be used for studying molecular machinery and spatiotemporal dynamics of other cellular processes.",

keywords = "STORM imaging, hidden Markov model, image modeling, intracellular transport, principal component analysis, spatial density estimation, spatiotemporal dynamics, super-resolution imaging",

author = "Chen, {Kuan Chieh} and Minhua Qiu and Jelena Kovacevic and Ge Yang",

year = "2014",

doi = "10.1007/978-3-319-09994-1_30",

language = "English (US)",

isbn = "9783319099934",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "292--303",

booktitle = "Computational Modeling of Objects Presented in Images",

note = "4th International Conference on Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications, CompIMAGE 2014 ; Conference date: 03-09-2014 Through 05-09-2014",

}

TY - GEN

T1 - Computational image modeling for characterization and analysis of intracellular cargo transport

AU - Chen, Kuan Chieh

AU - Qiu, Minhua

AU - Kovacevic, Jelena

AU - Yang, Ge

PY - 2014

Y1 - 2014

N2 - Active intracellular cargo transport is essential to survival and function of eukaryotic cells. How this process is controlled spatially and temporally so that the right cargo is delivered to the right destination at the right time remains poorly understood. To address this question, it is essential to characterize and analyze the molecular machinery and spatiotemporal behavior of intracellular transport. To this end, we developed related computational image models. Specifically, to study the molecular machinery of intracellular transport, we developed anisotropic spatial density kernels for reconstruction and segmentation of related super-resolution STORM (stochastic optical reconstruction microscopy) images. To study the spatiotemporal behavior of intracellular transport, we developed hidden Markov models and principal component analysis for representation and analysis of movement of individual transported cargoes. We validated and benchmarked the image models using simulated and actual experimental images. The models and related computational analysis methods developed in this study are general and can be used for studying molecular machinery and spatiotemporal dynamics of other cellular processes.

AB - Active intracellular cargo transport is essential to survival and function of eukaryotic cells. How this process is controlled spatially and temporally so that the right cargo is delivered to the right destination at the right time remains poorly understood. To address this question, it is essential to characterize and analyze the molecular machinery and spatiotemporal behavior of intracellular transport. To this end, we developed related computational image models. Specifically, to study the molecular machinery of intracellular transport, we developed anisotropic spatial density kernels for reconstruction and segmentation of related super-resolution STORM (stochastic optical reconstruction microscopy) images. To study the spatiotemporal behavior of intracellular transport, we developed hidden Markov models and principal component analysis for representation and analysis of movement of individual transported cargoes. We validated and benchmarked the image models using simulated and actual experimental images. The models and related computational analysis methods developed in this study are general and can be used for studying molecular machinery and spatiotemporal dynamics of other cellular processes.

KW - STORM imaging

KW - hidden Markov model

KW - image modeling

KW - intracellular transport

KW - principal component analysis

KW - spatial density estimation

KW - spatiotemporal dynamics

KW - super-resolution imaging

UR - http://www.scopus.com/inward/record.url?scp=84905864404&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84905864404&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-09994-1_30

DO - 10.1007/978-3-319-09994-1_30

M3 - Conference contribution

AN - SCOPUS:84905864404

SN - 9783319099934

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 292

EP - 303

BT - Computational Modeling of Objects Presented in Images

PB - Springer Verlag

T2 - 4th International Conference on Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications, CompIMAGE 2014

Y2 - 3 September 2014 through 5 September 2014

ER -

Computational image modeling for characterization and analysis of intracellular cargo transport

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this