The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Feature Set for Cytometry on Digitized Microscopic Images
Open accessAbstract
Feature extraction is a crucial step in most cytometry studies. In this paper a systematic approach to feature extraction is presented. The feature sets that have been developed and used for quantitative cytology at the Laboratory for Biomedical Image Analysis of the GSF as well as at the Center for Image Analysis in Uppsala over the last 25 years are described and illustrated. The feature sets described are divided into morphometric, densitometric, textural and structural features. The latter group is used to describe the eu‐ and hetero‐chromatin in a way complementing the textural methods. The main goal of the paper is to bring attention to the need of a common and well defined description of features used in cyto‐ and histometrical studies. The application of the sets of features is shown in an overview of projects from different fields. Finally some rules of thumb for the design of studies in this field are proposed. Colour figures can be viewed on http://www.esacp.org/acp/2003/25‐1/rodenacker.htm.
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Cites
Textural Features for Image Classification
Haralick, R. M., Shanmugam, K., & Dinstein, I. (1973) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1973.4309314 · Cited by 22,886
Cited by
Histopathological Image Analysis: A Review
Gurcan, M. N., Boucheron, L. E., Can, A., Madabhushi, A., Rajpoot, N. M., & Yener, B. (2009) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2009.2034865 · Cited by 2,052
Data-analysis strategies for image-based cell profiling
Caicedo, J. C., Cooper, S., Heigwer, F., Warchal, S., Qiu, P., Molnar, C., Vasilevich, A. S., Barry, J. D., Bansal, H. S., Kraus, O., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4397 · Cited by 739
WND-CHARM: Multi-purpose image classification using compound image transforms
Orlov, N., Shamir, L., Macura, T., Johnston, J., Eckley, D. M., & Goldberg, I. G. (2008) · Pattern Recognition Letters · doi:10.1016/j.patrec.2008.04.013 · Cited by 265
Automated visual classification of frequent defects in flat steel coils
Medina, R., Gayubo, F., González-Rodrigo, L. M., Olmedo, D., Gómez-García-Bermejo, J., Zalama, E., & Perán, J. R. (2011) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-011-3352-0 · Cited by 49
Metadata
- Authors
- Rodenacker, K., & Bengtsson, E.
- Venue
- Analytical Cellular Pathology
- Publisher
- Wiley
- Published
- 2002-10-10
- Volume
- 25
- Issue
- 1
- Pages
- 1-36
- ISSN
- 0921-8912 (ISSN-L)
- 2210-7177
- 2210-7185
- OpenAlex
- W2142082953
- Cited by
- 213
- References
- 1
- FWCI
- 6.17
- Type
- journal article
- Language
- en
- Open access
- gold
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- Rodenacker, K., & Bengtsson, E. (2003). A Feature Set for Cytometry on Digitized Microscopic Images. Analytical Cellular Pathology. https://doi.org/10.1155/2003/548678
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