ImageMiner: a software system for comparative analysis of tissue microarrays using content-based image retrieval, high-performance computing, and grid technology
Open accessAbstract
OBJECTIVE AND DESIGN: The design and implementation of ImageMiner, a software platform for performing comparative analysis of expression patterns in imaged microscopy specimens such as tissue microarrays (TMAs), is described. ImageMiner is a federated system of services that provides a reliable set of analytical and data management capabilities for investigative research applications in pathology. It provides a library of image processing methods, including automated registration, segmentation, feature extraction, and classification, all of which have been tailored, in these studies, to support TMA analysis. The system is designed to leverage high-performance computing machines so that investigators can rapidly analyze large ensembles of imaged TMA specimens. To support deployment in collaborative, multi-institutional projects, ImageMiner features grid-enabled, service-based components so that multiple instances of ImageMiner can be accessed remotely and federated. RESULTS: The experimental evaluation shows that: (1) ImageMiner is able to support reliable detection and feature extraction of tumor regions within imaged tissues; (2) images and analysis results managed in ImageMiner can be searched for and retrieved on the basis of image-based features, classification information, and any correlated clinical data, including any metadata that have been generated to describe the specified tissue and TMA; and (3) the system is able to reduce computation time of analyses by exploiting computing clusters, which facilitates analysis of larger sets of tissue samples.
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- Authors
- Foran, D. J., Yang, L., Chen, W., Hu, J., Goodell, L. A., Reiss, M., Wang, F., Kurc, T., Pan, T., Sharma, A., & Saltz, J. H.
- Affiliations
- Rutgers Cancer Institute (US)
- Emory University (US)
- Corresponding author
- Chen, Wenjin
- ORCID
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-07
- Volume
- 18
- Issue
- 4
- Pages
- 403-415
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC3128405
- OpenAlex
- W2124752499
- Cited by
- 65
- References
- 72
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 3 · 2022: 3 · 2021: 4 · 2020: 5 · 2019: 5 · 2018: 4 · 2017: 7 · 2016: 10 · 2015: 8 · 2014: 5 · 2013: 3 · 2012: 4
- FWCI
- 4.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (0615155, 0403342, DE-AC02–06CH11357)
- U.S. Department of Energy (DE‐ AC02‐06CH11357, AC02‐06CH11357, 06CH11357, DE-AC02-)
- U.S. Department of Health and Human Services
- National Institutes of Health (n01co12400-79-0-22, N01-CO-12400, DE-AC02–06CH11357, NIH U54, UL1TR000454, 5p20eb000591-03)
- U.S. Public Health Service (79077CBS10, 94995NBS23, 85983CBS43, 29XS154)
- National Heart, Lung, and Blood Institute (R24HL085343)
- National Cancer Institute (N01CO12400, N01-CO-012400, DE-AC02-06CH11357, U24CA180924, U54CA113001, R01CA156386, P30CA072720)
- National Institute of Biomedical Imaging and Bioengineering (P20-EB000591)
- U.S. National Library of Medicine (R01LM011119, R01LM009239)
- National Center for Research Resources (UL1RR025008)
- National Center for Advancing Translational Sciences
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Keywords
- tissue microarray, content-based image retrieval, high-performance computing, grid computing, service-oriented architecture, image registration, image segmentation, feature extraction, tumor detection, pathology informatics, microscopy image analysis
- MeSH terms
- Database Management Systems, Humans, Image Processing, Computer-Assisted, Software Design, United States, Information Dissemination, Tissue Array Analysis, Data Mining
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