High-performance systems for in silico microscopy imaging studies

Fusheng Wang; Tahsin Kurc; Patrick Widener; Tony Pan; Jun Kong; Lee Alex Donald Cooper; David Gutman; Ashish Sharma; Sharath Cholleti; Vijay Kumar; Joel Saltz

doi:10.1007/978-3-642-15120-0_2

High-performance systems for in silico microscopy imaging studies

Fusheng Wang^*, Tahsin Kurc, Patrick Widener, Tony Pan, Jun Kong, Lee Alex Donald Cooper, David Gutman, Ashish Sharma, Sharath Cholleti, Vijay Kumar, Joel Saltz

^*Corresponding author for this work

Pathology

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

4 Scopus citations

Abstract

High-resolution medical images from advanced instruments provide rich information about morphological and functional characteristics of biological systems. However, most of the information available in biomedical images remains underutilized in research projects. In this paper, we discuss the requirements and design of system support for composing, executing, and exploring in silico experiments involving microscopy images. This framework aims to provide building blocks for large scale, high-performance analytical image exploration systems, through rich metadata models, comprehensive query and data access capabilities, and efficient database and HPC support.

Original language	English (US)
Title of host publication	Data Integration in the Life Sciences - 7th International Conference, DILS 2010, Proceedings
Pages	3-18
Number of pages	16
DOIs	https://doi.org/10.1007/978-3-642-15120-0_2
State	Published - 2010
Event	7th International Conference on Data Integration in the Life Sciences, DILS 2010 - Gothenburg, Sweden Duration: Aug 25 2010 → Aug 27 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6254 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Data Integration in the Life Sciences, DILS 2010
Country/Territory	Sweden
City	Gothenburg
Period	8/25/10 → 8/27/10

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-15120-0_2

Cite this

Wang, F., Kurc, T., Widener, P., Pan, T., Kong, J., Cooper, L. A. D., Gutman, D., Sharma, A., Cholleti, S., Kumar, V., & Saltz, J. (2010). High-performance systems for in silico microscopy imaging studies. In Data Integration in the Life Sciences - 7th International Conference, DILS 2010, Proceedings (pp. 3-18). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6254 LNBI). https://doi.org/10.1007/978-3-642-15120-0_2

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title = "High-performance systems for in silico microscopy imaging studies",

abstract = "High-resolution medical images from advanced instruments provide rich information about morphological and functional characteristics of biological systems. However, most of the information available in biomedical images remains underutilized in research projects. In this paper, we discuss the requirements and design of system support for composing, executing, and exploring in silico experiments involving microscopy images. This framework aims to provide building blocks for large scale, high-performance analytical image exploration systems, through rich metadata models, comprehensive query and data access capabilities, and efficient database and HPC support.",

author = "Fusheng Wang and Tahsin Kurc and Patrick Widener and Tony Pan and Jun Kong and Cooper, {Lee Alex Donald} and David Gutman and Ashish Sharma and Sharath Cholleti and Vijay Kumar and Joel Saltz",

year = "2010",

doi = "10.1007/978-3-642-15120-0_2",

language = "English (US)",

isbn = "3642151191",

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

pages = "3--18",

booktitle = "Data Integration in the Life Sciences - 7th International Conference, DILS 2010, Proceedings",

note = "7th International Conference on Data Integration in the Life Sciences, DILS 2010 ; Conference date: 25-08-2010 Through 27-08-2010",

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Wang, F, Kurc, T, Widener, P, Pan, T, Kong, J, Cooper, LAD, Gutman, D, Sharma, A, Cholleti, S, Kumar, V & Saltz, J 2010, High-performance systems for in silico microscopy imaging studies. in Data Integration in the Life Sciences - 7th International Conference, DILS 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6254 LNBI, pp. 3-18, 7th International Conference on Data Integration in the Life Sciences, DILS 2010, Gothenburg, Sweden, 8/25/10. https://doi.org/10.1007/978-3-642-15120-0_2

High-performance systems for in silico microscopy imaging studies. / Wang, Fusheng; Kurc, Tahsin; Widener, Patrick et al.
Data Integration in the Life Sciences - 7th International Conference, DILS 2010, Proceedings. 2010. p. 3-18 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6254 LNBI).

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

TY - GEN

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AU - Wang, Fusheng

AU - Kurc, Tahsin

AU - Widener, Patrick

AU - Pan, Tony

AU - Kong, Jun

AU - Cooper, Lee Alex Donald

AU - Gutman, David

AU - Sharma, Ashish

AU - Cholleti, Sharath

AU - Kumar, Vijay

AU - Saltz, Joel

PY - 2010

Y1 - 2010

N2 - High-resolution medical images from advanced instruments provide rich information about morphological and functional characteristics of biological systems. However, most of the information available in biomedical images remains underutilized in research projects. In this paper, we discuss the requirements and design of system support for composing, executing, and exploring in silico experiments involving microscopy images. This framework aims to provide building blocks for large scale, high-performance analytical image exploration systems, through rich metadata models, comprehensive query and data access capabilities, and efficient database and HPC support.

AB - High-resolution medical images from advanced instruments provide rich information about morphological and functional characteristics of biological systems. However, most of the information available in biomedical images remains underutilized in research projects. In this paper, we discuss the requirements and design of system support for composing, executing, and exploring in silico experiments involving microscopy images. This framework aims to provide building blocks for large scale, high-performance analytical image exploration systems, through rich metadata models, comprehensive query and data access capabilities, and efficient database and HPC support.

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SN - 3642151191

SN - 9783642151194

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

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BT - Data Integration in the Life Sciences - 7th International Conference, DILS 2010, Proceedings

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Wang F, Kurc T, Widener P, Pan T, Kong J, Cooper LAD et al. High-performance systems for in silico microscopy imaging studies. In Data Integration in the Life Sciences - 7th International Conference, DILS 2010, Proceedings. 2010. p. 3-18. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-15120-0_2

High-performance systems for in silico microscopy imaging studies

Abstract

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Conference

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