Quantifying Cell Scattering: The Blob Algorithm Revisited

Cytometry Part A

Volumn 51, Issue 2, 2003, Pages 119-126

  Kort, Eric J ^a   Jones, Ashley ^b   Daumbach, Michael ^b   Hudson, Eric A ^a   Buckner, Bree ^a   Resau, James H ^a  

^a VAN ANDEL RESEARCH INSTITUTE   (United States)

^b NATIONAL CANCER INSTITUTE   (United States)

Author keywords

Blob algorithm; Cell scattering; Computer assisted image analysis; Hepatocyte growth factor receptor

Indexed keywords

SCATTER FACTOR RECEPTOR;

ALGORITHM; ANIMAL CELL; ARTICLE; CELL ACTIVITY; CELL COUNT; CELL SCATTERING; CELL SIZE; CELL SORTER; CELL STRAIN; CONTROLLED STUDY; FLOW CYTOMETRY; IMAGE ANALYSIS; NONHUMAN; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; SCORING SYSTEM;

EID: 0346244103     PISSN: 15524922     EISSN: None     Source Type: Journal    
DOI: 10.1002/cyto.a.10010     Document Type: Article

References (34)

1. Page D. Prognosis and breast cancer. Recognition of lethal and favorable prognostic types. Am J Surg Pathol 1991;15:334-349.
2. Jones D, Fletcher C. How shall we apply the new biology to diagnostics in surgical pathology? J Pathol 1999;187:147-154.
3. Delides G, Garas G, Georgouli G, Jiortziotis D, Lecca J, Liva T, Elemenoglou J. Intralaboratory variations in the grading of breast carcinoma. Arch Pathol Lab Med 1982;106:126-128.
4. Boiesen P, Bendahl P, Anagnostaki L, Domanski H, Holm E, Idvall I, Johansson S, Ljungberg O, Ringberg A, Ostberg G, Ferno M. Histologic grading in breast cancer-reproducibility between seven pathologic departments. South Sweden Breast Cancer Group. Acta Oncol 2000;39:41-45.
5. Sloane J, Amendoeira I, Apostolikas N, Bellocq J, Bianchi S, Boecker W, Bussolati G, Coleman D, Connolly C, Eusebi V, De-Miguel C, Dervan P, Drijkoningen R, Elston C, Faverly D, Gad A, Jacquemier J, Lacerda M, Martinez-Penuela J, Munt C, Peterse J, Rank F, Sylvan M, Tsakraklides V, Zafrani B. Consistency achieved by 23 European pathologists from 12 countries in diagnosing breast disease and reporting prognostic features of carcinomas. European Commission Working Group on Breast Screening Pathology. Virchows Arch 1999;434:3-10.
6. Kronqvist P, Montironi R, Kuopio T, Collan Y. Subjective breast cancer grading. Analyses of reproducibility after application of Bayesian belief networks. Anal Quant Cytol Histol 1997;19:423-429.
7. Toczek H, Fritz P, Schwarzmann P, Wu X, Mahner G. Breast carcinoma, correlations between visual diagnostic criteria for histologic grading and features of image analysis Analyt Quant Cytol Histol 1996;18:481-493.
8. Layfield L, Saria E, Mooney E, Liu K, Dodge R. Tissue heterogeneity of immunohistochemically detected estrogen receptor. Implications for image analysis quantification. Am J Clin Pathol 1998;110:758-764.
9. Neri T, Carnevali L, Orlandini G, Gatti R, Scandroglio R, Savi M, Allegri L. Fluorescent in situ hybridisation on tissue sections: a quantitative approach with confocal laser scanning microscopy. Eur J Histochem 2000;44:193-198.
10. Bogardus S, Concato J, Feinstein A. Clinical epidemiological quality in molecular genetic research: the need for methodological standards. JAMA 1999;281:1919-1926.
11. Tsarfaty I, Alvord W, Resau J, Altstock R, Lidereau R, Bieche I, Bertrand F, Horev J, Klabansky, R, Keydar I, Vande-Woude G. Alteration of Met protooncogene product expression and prognosis in breast carcinomas. Anal Quant Cytol Histol 1999;21:397-408.
12. Altstock R, Stein G, Resau J, Tsarfaty I. Algorithms for quantitation of protein expression variation in normal versus tumor tissue as a prognostic factor in cancer: Met oncogene expression, and breast cancer as a model. Cytometry 2000;41:155-165.
13. Thiel S, Wiltshire R, Davies L. Automated object recognition of blue-green algae for measuring water quality - a preliminary study. Water Res 1995;29:2398-2404.
14. Pla F, Ferri F. Feature extraction of spherical objects in image analysis: an application to robotic citrus harvesting. Comput Electron Agric 1993;8:57-72.
15. Cootes T, Page G, Jackson C, Taylor C. Statistical grey-level models for object location and identification. Image Vis Comput 1996;14:533-540.
16. Oberholzer M, Ostreicher M, Christen H, Bruhlmann M. Methods in quantitative image analysis. Histochem Cell Biol 1996;105:333-355.
17. Berube J. Geometric object location is highly robust. Laser Focus World 2000;36:191-195.
18. Seul M, O'Gorman L, Sammon M. Practical algorithms for image analysis: descriptions, examples, and code. Cambridge: Cambridge University Press; 2000.
19. Ridler T, Calvard S. Picture thresholding using an iterative selection method. IEEE Trans Systems Man Cybernet 1978;SMC-8:630-632.
20. VandeWoude G, Jeffers M, Cortner J, Alvord G, Tsarfaty I, Resau J. Met·HGF/SF: tumorigenesis, invasion and metastasis. Ciba Found Symp 1997;21:119-130.
21. DiRenzo M, Narsimhan R, Olivero M, Bretti S, Giordano S, Medico E, Gagha P, Zara P, Comoglio P. Expression of the Met/HGF receptor in normal and neoplastic human tissues. Oncogene 1991;6:1997-2003.
22. Tajima H, Matsumoto K, Nakamura T. Regulation of cell growth and motility by hepatocyte growth factor and receptor expression in various cell species. Exp Cell Res 1992;202:423-431.
23. Zahm J, Debordeaux C, Raby B, Klossek J, Bonnet N, Puchelle E. Mitogenic effect of recombinant HGF on airway epithelial cells during the in vitro wound repair of the respiratory epithelium. J Cell Physiol 2000;185:447-453.
24. Tsarfaty I, Resau J, Rulong S, Keydar I, Faletto D, VandeWoude G. The met proto-oncogene receptor and lumen formation. Science 1992;257:1258-1261.
25. Bussolino F, DiRenzo M, Ziche M, Bocchietto E, Olivero M, Naldini L, Gaudino G, Tamagnone L, Coffer A, Comoglio P. Hepatocyte growth factor is a potent angiogenic factor which stimulates endothelial cell motility and growth. J Cell Biol 1992;119:629-641.
26. Niranjan B, Buluwela L, Yant J, Perusinghe N, Atherton A, Phippard D, Dale T, Gusterson B, Kamalati T. HGF/SF: a potent cytokine for mammary growth, morphogenesis and development. Development 1995;121:2897-2908.
27. Harvey P, Clark I, Jaurand M, Warn R, Edwards D. Hepatocyte growth factor/scatter factor enhances the invasion of mesothelioma cell lines and the expression of matrix metalloproteinases. Br J Cancer 2000;83:1147-1153.
28. Ihaka R, Gentleman R. R: a language for data analysis and graphics. J Comput Graph Stat 1996;5:299-314.
29. Grizzle W, Aamodt R, Clausen K, LiVolsi V, Pretlow T, Qualman S. Providing human tissues for research: how to establish a program. Arch Pathol Lab Med 1998;122:1065-1076.
30. Hanahan D, Weinberg R. The hallmarks of cancer. Cell 2000;100:57-70.
31. Wallis Y, Macdonald F. Demystified ... oncogenes. Mol Pathol 1999;52:55-63.
32. Iwamoto K, Mizuno T, Ito T, Akiyama M, Takeichi N, Mabuchi K, Seyama T. Feasibility of using decades-old archival tissues in molecular oncology/epidemiology. Am J Pathol 1996;149:399-406.
33. Kleeberger C, Lyles R, Margolick J, Rinaldo C, Phair J, Giorgi J. Viability and recovery of peripheral blood mononuclear cells cryopreserved for up to 12 years in a multicenter study. Clin Diagn Lab Immunol 1999;6:14-19.
34. Bottaro D, Rubin J, Faletto D, Chan A, Kmiecik T, VandeWoude G, Aaronson S. Identification of the hepatocyte growth factor receptor as the c-met proto-oncogene product. Science 1991;251:802-804.