CP-CHARM: Segmentation-free image classification made accessible

BMC Bioinformatics

Volumn 17, Issue 1, 2016, Pages

  Uhlmann, Virginie ^a,b   Singh, Shantanu ^b   Carpenter, Anne E ^b  

^a EPFL   (Switzerland)

^b BROAD INSTITUTE OF MIT AND HARVARD   (United States)

Author keywords

Biological imaging; High dimensional classification; Image classification; Image features; Segmentation free analysis

Indexed keywords

IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE SEGMENTATION; LEARNING SYSTEMS; OPEN SOURCE SOFTWARE; OPEN SYSTEMS;

AUTOMATED CLASSIFICATION; BIOLOGICAL IMAGING; CLASSIFICATION ACCURACY; CLASSIFICATION ALGORITHM; HIGH-DIMENSIONAL; IMAGE FEATURES; IMAGE-BASED CLASSIFICATION; MORPHOLOGICAL FEATURES;

CLASSIFICATION (OF INFORMATION);

ARTIFACT; BIOLOGY; CLASSIFICATION; CLASSIFICATION ALGORITHM; COMPUTER PROGRAM; EXTRACT; EXTRACTION; HUMAN; IMAGE ANALYSIS; ORGAN CULTURE; PIPELINE; SCIENTIST; ALGORITHM; AUTOMATED PATTERN RECOGNITION; CELLS; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; FLUORESCENCE MICROSCOPY; PROCEDURES; SOFTWARE;

ALGORITHMS; ARTIFACTS; CELLS; COMPUTATIONAL BIOLOGY; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY, FLUORESCENCE; PATTERN RECOGNITION, AUTOMATED; SOFTWARE;

EID: 84956574418     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-0895-y     Document Type: Article

References (36)

1. Rui Y, Huang TS, Chang SF. Image retrieval: Current techniques, promising directions, and open issues. J Vis Commun Image Represent. 1999; 10(1):39-62.
2. Vailaya A, Figueiredo MAT, Jain AK, Zhang HJ. Image classification for content-based indexing. IEEE Trans Image Process. 2001; 10(1):117-30.
3. Huang K, Murphy RF. Automated classification of subcellular patterns in multicell images without segmentation into single cells. In: Proceedings of the IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'04): April 15-18. Arlington: IEEE: 2004. p. 1139-42.
4. Glory E, Murphy RF. Automated subcellular location determination and high-throughput microscopy. Dev Cell. 2007; 12(1):7-16.
5. Yang F, Xu YY, Shen HB. Many local pattern texture features: which is better for image-based multilabel human protein subcellular localization classification?Sci World J. 2014; 2014:429049.
6. Iannello G, Onofri L, Soda P. A bag of visual words approach for centromere and cytoplasmic staining pattern classification on hep-2 images. In: Proceedings of the 25th International Symposium on Computer-based Medical Systems (CBMS'12): June 20-22. Rome: IEEE: 2012. p. 1-6.
7. Rajaram S, Pavie B, Wu LF, Altschuler SJ. Phenoripper: software for rapidly profiling microscopy images. Nature methods. 2012; 9(7):635-7.
8. Zhou J, Lamichhane S, Sterne G, Ye B, Peng H. Biocat: a pattern recognition platform for customizable biological image classification and annotation. BMC Bioinforma. 2013; 14(1):291.
9. Shamir L, Orlov N, Eckley DM, Macura T, Johnston J, Goldberg IG. Wndchrm- an open source utility for biological image analysis. BMC Source Source Code Biol Med. 2008; 3:13.
10. Orlov N, Shamir L, Macura T, Johnston J, Eckley DM, Goldberg IG. Wnd-charm: Multi-purpose image classification using compound image transforms. Pattern Recogn Lett. 2008; 29(11):1684-93.
11. Shamir L, Orlov N, Eckley DM, Macura TJ, Goldberg IG. Iicbu 2008: a proposed benchmark suite for biological image analysis. Med Biol Eng Comput. 2008; 46(9):943-7.
12. Shamir L. Assessing the efficacy of low-level image content descriptors for computer-based fluorescence microscopy image analysis. J Microsc. 2011; 243(3):284-92.
13. Coelho LP, Kangas JD, Naik AW, Osuna-Highley E, Glory-Afshar E, Fuhrman M, et al. Determining the subcellular location of new proteins from microscope images using local features. Bioinformatics. 2013; 29(18):2343-9.
14. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, et al. Cellprofiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 2006; 7(10):100.
15. Kamentsky L, Jones TR, Fraser A, Bray MA, Logan DJ, Madden KL, et al. Improved structure, function and compatibility for cellprofiler: modular high-throughput image analysis software. Bioinformatics. 2011; 27(8):1179-80.
16. Lamprecht MR, Sabatini DM, Carpenter AE. Cellprofiler™: free, versatile software for automated biological image analysis. Biotechniques. 2007; 42(1):71.
17. Wiesmann V, Franz D, Held C, Münzenmayer C, Palmisano R, Wittenberg T. Review of free software tools for image analysis of fluorescence cell micrographs. J Microsc. 2015; 257(1):39-53.
18. Ljosa V, Sokolnicki KL, Carpenter AE. Annotated high-throughput microscopy image sets for validation. Nat Methods. 2012; 9(7):637.
19. Uhlen M, Oksvold P, Fagerberg L, Lundberg E, Jonasson K, Forsberg M, et al. Towards a knowledge-based human protein atlas. Nat Biotechnol. 2010; 28(12):1248-50.
20. Uhlmann V. A segmentation-free image classifier for biological applications. Master's thesis. Swiss Federal Institute of Technology, Lausanne (EPFL) (2012) https://documents.epfl.ch/users/v/vu/vuhlmann/www/Uhlmann2012.
21. Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: Machine learning in python. J Mach Learn Res. 2011; 12:2825-830.
22. Murphy RF, Velliste M, Porreca G. Robust numerical features for description and classification of subcellular location patterns in fluorescence microscope images. J VLSI Signal Process Syst Signal Image Video Technol. 2003; 35(3):311-21.
23. Shamir L, Delaney JD, Orlov N, Eckley DM, Goldberg IG. Pattern recognition software and techniques for biological image analysis. PLoS Comput Biol. 2010; 6(11):e1000974.
24. Jolliffe IT. Principal Component Analysis, 2nd ed. New York: Springer-Verlag; 2002.
25. Peng H, Long F, Ding C. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell. 2005; 27(8):1226-38.
26. Huang K, Velliste M, Murphy RF. Feature reduction for improved recognition of subcellular location patterns in fluorescence microscope images. In: Proceedings of SPIE 4962, Manipulation and Analysis of Biomolecules, Cells, and Tissues. San Jose, CA, United States: The International Society for Optical Engineering: 2003. p. 307-18. International Society for Optics and Photonics.
27. Friedman JH. Regularized discriminant analysis. J Am Stat Assoc. 1989; 84(405):165-75.
28. Ye J, Xiong T, Li Q, Janardan R, Bi J, Cherkassky V, et al. Efficient model selection for regularized linear discriminant analysis. In: Proceedings of the Fifteenth ACM International Conference on Information and Knowledge Management (CIKM'06): November 5-11. Arlington, VA, USA: ACM: 2006. p. 532-9.
29. Dillon WR, Goldstein M. Multivariate Analysis: Methods and Applications. New York: Wiley; 1984.
30. McLachlan G. Discriminant Analysis and Statistical Pattern Recognition. New York: Wiley; 2004.
31. Kuhn M, Weston S, Williams A, Keefer C, Engelhardt A, Contributions from Wing J. Caret: Classification and Regression Training. 2012. R package version 5.15-044. http://CRAN.R-project.org/package=caret. Accessed 21 July 2015.
32. Kohavi R. A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'95): August 20-25. Montreal, Canada: AAAI Press / International Joint Conferences on Artificial Intelligence: 1995. p. 1137-45.
33. Git Repository of CP-CHARM. https://github.com/CellProfiler/CPCharm. Accessed 20 Sept 2015.
34. Logan DJ, Carpenter AE. Screening cellular feature measurements for image-based assay development. J Biomol Screen. 2010; 15(7):840-6.
35. Swamidoss IN, Kårsnäs A, Uhlmann V, Ponnusamy P, Kampf C, Simonsson M, et al. Automated classification of immunostaining patterns in breast tissue from the human protein atlas. J Pathol Inf. 2013; 4(Suppl):S14.
36. Previous Releases of CellProfiler. http://www.cellprofiler.org/previousReleases.shtml. Accessed 20 Sept 2015.