Automated recognition of patterns characteristic of subcellular structures in fluorescence microscopy images

Cytometry

Volumn 33, Issue 3, 1998, Pages 366-375

  Boland, Michael V ^a   Markey, Mia K ^a   Murphy, Robert F ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Fluorescence; Microscopy; Neural networks (computer); Pattern recognition; Protein localization; Subcellular location; Zernike moments

Indexed keywords

ANIMAL CELL; ARTICLE; AUTOMATION; CELL STRUCTURE; CELLULAR DISTRIBUTION; CHO CELL; FLUORESCENCE MICROSCOPY; NONHUMAN; PRIORITY JOURNAL; PROTEIN LOCALIZATION;

IMAGE ENHANCEMENT; IMAGE PROCESSING, COMPUTER-ASSISTED; MICROSCOPY, FLUORESCENCE; PATTERN RECOGNITION, AUTOMATED; PROTEINS;

ANIMALIA;

EID: 0032212323     PISSN: 01964763     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1097-0320(19981101)33:3<366::AID-CYTO12>3.0.CO;2-R     Document Type: Article

References (30)

1. Agard DA, Hiraoka Y, Shaw P, Sedat JW: Fluorescence microscopy in three dimensions. In: Fluorescence Microscopy of Living Cells in Culture, Methods in Cell Biology, Vol. 30, Taylor DL, Wang Y-L (eds). Academic Press, Inc., San Diego, CA, 1989, pp. 353-377.
2. Bailey RR, Mandyam S: Orthogonal moment features for use with parametric and non-parametric classifiers. IEEE Trans Pattern Anal Machine Intell 18:389-399, 1996.
3. Belkasim SO, Shridhar M, Ahmadi M: Pattern recognition with moment invariants: A comparative study and new results. Pattern Recognit 24:1117-1138, 1991.
4. Birdsong GG: Automated screening of cervical cytology specimens. Hum Pathol 27:468-481, 1996.
5. Born M, Wolf E: Principles of Optics, 2nd Edition. Pergamon Press Ltd., Oxford, England, 1964.
6. Breiman L, Friedman JH, Olshen RA, Stone CJ: Classification and Regression Trees. Wadsworth and Brooks/Cole, Monterey, CA, 1984.
7. Burns N, Grimwade B, Ross-Macdonald PB, Choi EY, Finberg K, Roeder GS, Snyder M: Large-scale analysis of gene expression, protein localization, and gene disruption in Saccharomyces cerevisiae. Genes Dev 8:1087-1105, 1994.
8. Duda RO, Hart PE: Pattern Classification and Scene Analysis. John Wiley & Sons, New York, 1973.
9. Farkas DL, Baxter G, DeBiasio RL, Gough A, Nederlof MA, Pane D, Patek DR, Ryan KW, Taylor DL: Multimode light microscopy and the dynamics of molecules, cells, and tissues. Ann Rev Physiol 55:785-817, 1993.
10. Fleming MG: Design of a high resolution image cytometer with open software architecture. Anal Cell Pathol 10:1-11, 1996.
11. Granger BL, Green SA, Gabel CA, Howe CL, Mellman I, Helenius A: Characterization and cloning of Igp110, a lysosomal membrane glycoprotein from mouse and rat cells. J Biol Chem 265:12036-12043, 1990.
12. Haralick RM: Statistical and structural approaches to texture. Proc IEEE 67:786-804, 1979.
13. Hornick K, Stinchcombe M, White H: Multilayer feedforward networks are universal approximators. Neural Netw 2:359-366, 1989.
14. Hu M-K: Visual pattern recognition by moment invariants. IRE Trans Inf Theory IT 8:179-187, 1962.
15. Jaggi B, Poon SS, MacAulay C, Palcic B: Imaging system for morphometric assessment of absorption or fluorescence in stained cells. Cytometry 9:566-572, 1988.
16. Khotanzad A, Hong YH: Invariant image recognition by Zernike moments. IEEE Trans Pattern Anal Machine Intell 12:489-497, 1990.
17. Khotanzad A, Hong YH: Rotation invariant image recognition using features selected via a systematic method. Pattern Recognit 23:1089-1101, 1990.
18. Khotanzad A, Lu J-H: Classification of invariant image representations using a neural network. IEEE Trans Acoust Speech Signal Process 38:1028-1038, 1990.
19. Klecka WR: Discriminant analysis. In: Quantitative Applications in the Social Sciences, Vol. 19, Sullivan JL (ed). Sage University Paper, Beverly Hills and London, 1980.
20. Lee BR, Haseman DB, Reynolds CP: A digital image microscopy system for rare-event detection using fluorescent probes. Cytometry 10:256-262, 1989.
21. Linstedt AD, Hauri HP: Giantin, a novel conserved Golgi membrane protein containing a cytoplasmic domain of at least 350 kDa. Mol Biol Cell 4:679-693, 1993.
22. Lockett SJ, Jacobson K, Herman B: Quantitative precision of an automated, fluorescence-based image cytometer. Anal Quant Cytol Histol 14:187-202, 1992.
23. McClelland JL, Rumelhart DE: Parallel Distributed Processing: Explorations in the Microsctucture of Cognition. Vol. 1. The MIT Press, Cambridge, MA, 1986.
24. Nederlof PM, van der Flier S, Verwoerd NP, Vrolijk J, Raap AK, Tanke HJ: Quantification of fluorescence in situ hybridization signals by image cytometry. Cytometry 13:846-852, 1992.
25. Perantonis SJ, Lisboa PJG: Translation, rotation, and scale invariant pattern recognition by high-order neural networks and moment classifiers. IEEE Trans Neural Netw 3:241-251, 1992.
26. Sawin KE, Nurse P: Identification of fission yeast nuclear markers using random polypeptide fusions with green fluorescent protein. Proc Natl Acad Sci USA 93:15146-15151, 1996.
27. Sun C, Woolford IL, Jr.: The yeast NOP4 gene product is an essential nucleolar protein required for pre-rRNA processing and accumulation of 60S ribosomal subunits. EMBO J 13:3127-3135, 1994.
28. Teague MR: Image analysis via the general theory of moments. J Opt Soc Am 70:920-930, 1980.
29. Vrolijk H, Sloos WC, van de Rijke FM, Mesker WE, Netten H, Young IT, Raap AK, Tanke HJ: Automation of spot counting in interphase cytogenetics using brightfield microscopy. Cytometry 24:158-166, 1996.
30. Zernike F: Beugungstheorie des Schneidenverfarhens und Seiner Verbesserten Form, der Phasenkontrastmethode. Physica 1:689-704, 1934.