FahamecV1:A Low Cost Automated Metaphase Detection System


  • H. Yilmaz Computer Programming Department, TOBB Tech. Sciences Vocational School, Karabuk University, Karabuk, Turkey
  • M. Kamil Turan Biology and Genetics Department, Faculty of Medicine, Karabuk University, Karabuk, Turkey
Volume: 7 | Issue: 6 | Pages: 2160-2166 | December 2017 | https://doi.org/10.48084/etasr.1464


In this study, FahamecV1 is introduced and investigated as a low cost and high accuracy solution for metaphase detection. Chromosome analysis is performed at the metaphase stage and high accuracy and automated detection of the metaphase stage plays an active role in decreasing analysis time. FahamecV1 includes an optic microscope, a motorized microscope stage, an electronic control unit, a camera, a computer and a software application. Printing components of the motorized microscope stage (using a 3D printer) is of the main reasons for cost reduction. Operations such as stepper motor calibration, are detection, focusing, scanning, metaphase detection and saving of coordinates into a database are automatically performed. To detect metaphases, a filter named Metafilter is developed and applied. Average scanning time per preparate is 77 sec/cm2. True positive rate is calculated as 95.1%, true negative rate is calculated as 99.0% and accuracy is calculated as 98.8%.


automation, metaphase detection system, focus, image processing, 3D printing, FahamecV1


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J. Piper, M. Poggensee, W. Hill, R. Jensen, L. Ji, I. Poole, M. Stark, D. Sudar, “Automatic fluorescence metaphase finder speeds translocation scoring in FISH painted chromosomes”, Cytometry, Vol. 16, No. 1, pp. 7–16, 1994 DOI: https://doi.org/10.1002/cyto.990160103

R. Huber, U. Kulka, T. Lorch, H. Braselmann, M. Bauchinger, “Automated metaphase finding: an assessment of the efficiency of the METAFER2 system in a routine mutagenicity assay”, Mutation Research/Environmental Mutagenesis and Related Subjects, Vol. 334, No. 1, pp. 97–102, 1995 DOI: https://doi.org/10.1016/0165-1161(95)90035-7

A. Furukawa, M. Minamihisamatsu, I. Hayata, “Low-Cost Metaphase System”, Health Physics, Vol. 98, No. 2, pp. 269–275, 2010 DOI: https://doi.org/10.1097/HP.0b013e3181b357c1

F. Arambula Cosío, L. Vega, A. Herrera Becerra, C. Prieto Meléndez, G. Corkidi, “Automatic identification of metaphase spreads and nuclei using neural networks”, Medical & Biological Engineering & Computing, Vol. 39, No. 3, pp. 391–396, 2001 DOI: https://doi.org/10.1007/BF02345296

X. Wang, B. Zheng, S. Li, J. J. Mulvihill, M. C. Wood, H. Liu, “Automated classification of metaphase chromosomes: Optimization of an adaptive computerized scheme”, Journal of Biomedical Informatics, Vol. 42, No. 1, pp. 22–31, 2009 DOI: https://doi.org/10.1016/j.jbi.2008.05.004

Y. Qiu, J. Song, X. Lu, Y. Li, B. Zheng, S. Li, H. Liu, “Feature Selection for the Automated Detection of Metaphase Chromosomes: Performance Comparison Using a Receiver Operating Characteristic Method”, Analytical Cellular Pathology, Vol. 2014, pp. 1–9, 2014 DOI: https://doi.org/10.1155/2014/565392

L. Roy, V. Durand, M. Delbos, I. Sorokine-Durm, F. Soussaline, P. Voisin, “A New Image Analysis System for Biological Dosimetry by Fluorescent in situ Hybridization. Step 1: Metaphase Finder and Automatic Metaphase Acquisition Validation”, Journal of Radiation Research, Vol. 42, No. 2, pp. 165–177, 2001 DOI: https://doi.org/10.1269/jrr.42.165

K. Odawara, K. Yamamoto, H. Kato, M. Hara, K. Shigefumi, F. Kishida, A. Yoshitake, I. Nakatsuka, “A new semi-automated chromosome analysis system for in vitro chromosomal aberration tests”, Mutation Research/Genetic Toxicology and Environmental Mutagenesis, Vol. 389, No. 2–3, pp. 207–212, 1997 DOI: https://doi.org/10.1016/S1383-5718(96)00149-0

A. Furukawa, “The Project Of Another Low-Cost Metaphase Finder”, Radiation Protection Dosimetry, Vol. 172, No. 1–3, pp. 238–243, 2016 DOI: https://doi.org/10.1093/rpd/ncw152

K. R. Castleman, “The PSI Automatic Metaphase Finder”, Journal of Radiation Research, Vol. 33, Suplement, pp. 124–128, 1992 DOI: https://doi.org/10.1269/jrr.33.SUPPLEMENT_124

J. Weber, W. Scheid, H. Traut, “Time-saving in biological dosimetry by using the automatic metaphase finder Metafer2”, Mutation Research/Environmental Mutagenesis and Related Subjects, Vol. 272, No. 1, pp. 31–34, 1992 DOI: https://doi.org/10.1016/0165-1161(92)90006-8

X. Wang, B. Zheng, M. Wood, S. Li, W. Chen, H. Liu, “Development and evaluation of automated systems for detection and classification of banded chromosomes: current status and future perspectives”, Journal of Physics D: Applied Physics, Vol. 38, No. 15, pp. 2536–2542, 2005 DOI: https://doi.org/10.1088/0022-3727/38/15/003

G. Korthof, A. D. Carothers, “Tests of performance of four semiautomatic metaphase-finding and karyotyping systems”, Clinical Genetics, Vol. 40, No. 6, pp. 441–451, 2008 DOI: https://doi.org/10.1111/j.1399-0004.1991.tb03116.x

J. R. N. McLean, F. Johnson, “Evaluation of a metaphase chromosome finder: Potential application to chromosome-based radiation dosimetry”, Micron, Vol. 26, No. 6, pp. 489–492, 1995 DOI: https://doi.org/10.1016/0968-4328(95)00005-4

Q. Yuchen, C. Xiaodong, L. Yuhua, C. Wei R., Z. Bin, L. Shibo, L. Hong, “Evaluations of auto-focusing methods under a microscopic imaging modality for metaphase chromosome image analysis”, Analytical Cellular Pathology, Vol. 36, No. 1-2, pp. 37–44, 2013 DOI: https://doi.org/10.1155/2013/412920

D. Bradley, G. Roth, “Adaptive Thresholding using the Integral Image”, Journal of Graphics Tools, Vol. 12, No. 2, pp. 13–21, 2007 DOI: https://doi.org/10.1080/2151237X.2007.10129236

G. Corkidi, L. Vega, J. Márquez, E. Rojas, P. Ostrosky-Wegman, “Roughness feature of metaphase chromosome spreads and nuclei for automated cell proliferation analysis”, Medical & Biological Engineering & Computing, Vol. 36, No. 6, pp. 679–685, 1998 DOI: https://doi.org/10.1007/BF02518869


How to Cite

H. Yilmaz and M. Kamil Turan, “FahamecV1:A Low Cost Automated Metaphase Detection System”, Eng. Technol. Appl. Sci. Res., vol. 7, no. 6, pp. 2160–2166, Dec. 2017.


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