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JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI

Year 2013, Volume: 2 Issue: 3, 100 - 109, 01.09.2013

Güliz Toz Pakize Erdoğmuş Kadri Dönmez

Abstract

Gel blood grouping system is one of the most widely used methods of blood grouping systems. The devices and kits of this system which has also been widely used in our country are imported. In this study a software has been developed for the gel test reader device which is a part of the gel blood grouping system in order to manufacture the blood group system in our country. The developed software uses gel test samples which have 6 tubes for the detection of the blood groups. With this software, firstly the captured images of the samples are imported in the program and then the detection of blood group is achieved by using digital image processing techniques. The developed software has been tested by eight different gel test samples. Each of these samples includes one of the eight different blood groups (A Rh (+), A Rh (-), B Rh (+), B Rh (-), AB Rh (+), AB Rh (-) and O Rh (+), OR Rh (-)). The obtained results shown that the developed software can detect the blood groups with a high accuracy rate.

Keywords

Blood groups gel test method user interface design.

References

  • Malomgre, W., and Neumeister, B., (2009). Recent and Future Trends in Blood Group Typing, Anal Bioanal Chem, 393, 1443-1451.
  • Okroi, M., and Mccarthy, L. J., (2010). The Original Blood Group Pioneers: The Hirszfelds, Transfusion Medicine Reviews, 24, 244-246.
  • Landsteiner, K., and Wiener, A. S., (1940). An Agglutinable Factor in Human Blood Recognized by Immune Sera for Rhesus Blood, Exp Biol Med (Maywood), 43, 223.
  • Şentuna, C., (1982). Rh Gen Frekansları Yönünden Türkiye'nin Yeri, Ankara Üniversitesi Dil ve TarihCoğrafya Fakültesi Dergisi, 30, 153-179.
  • Lapierre, Y., Rigal, D., Adam, J., Josef, D., Meyer, F., Greber, S., and Drot, C., (1990). The Gel Test: A New Way To Detect Red Cell Antigen-Antibody Reactions, Transfusion, 30, 109-113. http://megep.meb.gov.tr/mte_program_modul/moduller_pdf/Uygunluk%20Testleri.pdf
  • Kim, S. W., and Kim, N. S., (2013). Dynamic Characteristics of Suspension Bridge Hanger Cables Using Digital Image Processing, NDT & E International, 59, 25-33.
  • Adelkhani, A., Beheshti, B., Minaei, S., Javadikia, P., and Ghasemi-Varnamkhasti, M., (2013). Taste Characterization of Orange Using Image Processing Combined with ANFIS, Measurement, 46, 3573-3580.
  • Shi, Q., Ishii, H., Konno, S., Kinoshita, S., and Takanishi, A., (2012). Image Processing and Behavior Planning for RobotRat İnteraction, 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 967-973.
  • Statella, T., Pina, P., and Antônio Da Silva, E., (2012). Image Processing Algorithm for the Identification of Martian Dust Devil Tracks in MOC and HiRISE Images, Planetary and Space Science, 70, 46-58.
  • Kouloulias, V. E., Dardoufas, C. E., Kouvaris, J. R., Antypas, C. E., Sandilos, P. H., Matsopoulos, G. K., and Vlahos, L. J., (2002). Use of Image Processing Techniques to
  • Assess Effect of Disodium Pamidronate in Conjunction with Radiotherapy in Patients with Bone Metastases, Acta Oncologica, 41, 169–174. Moore, S. T., Haslwanter, T., Curthoys, I. S., and Smith, S. T., (1996). A Geometric Basis for Measurement of Three-dimensional Eye Position Using Image Processing, Vision Research, 36, 445-459.
  • Van Der Vorst, J. R., Van Dam, R. M., Van Stiphout, R. S., Van Den Broek, M. A., Hollander, I. H., Kessels, A. G., and Dejong C. H., (2010). Virtual Liver Resection and Volumetric Analysis of the Future Liver Remnant using Open Source Image Processing
  • Software, World Journal of Surgery, 34, 2426-2433.
  • Weidenbach, M., Wick, C., Pieper, S., and Redel D. A., (2000). Augmented Reality in
  • Echocardiography. A New Method of Computer-Assisted Training and Image Processing Using Virtual and Real Three-Dimensional Data Sets, Zeitschrift für Kardiologie, 89, 1681
  • Sharma, P., Nirmala, S. R., and Sarma K. K., (2013). Classification of Retinal Images Using Image Processing Techniques, Journal of Medical Imaging and Health Informatics, 3, 341-346.
  • Lin, Q., Liang, Z., Duan, C., Ma, J., Li, H., Roque, C., Yang, J., Zhang, G., Lu, H., and He, X., (2013). Motion Correction for MR Cystography by an Image Processing Approach, IEEE Transactions on Biomedical Engineering, 60, 2401-2410.
  • Şirikçi, A., Bayazit, Y. A., Kervancioğlu, S., Ozer, E., Kanlikama, M., and Bayram, M., (2004). Assessment of Mastoid Air Cell Size Versus Sigmoid Sinus Variables with a
  • Tomography-Assisted Digital Image Processing Program and Morphometry, Surgical and Radiologic Anatomy, 26, 145–148. Benetazzo, L., Bizzego, A., De Caro, R., Frigo, G., Guidolin, D., and Stecco, C., (2011). 3D Reconstruction of the Crural and Thoracolumbar Fasciae, Surgical and Radiologic Anatomy, 33, 855-862.
  • Fathima, S. M. N., (2013). Classification of Blood Types by Microscope Color Images, International Journal of Machine Learning and Computing, 3, 376-379.
  • Ferraza, A., Carvalhoa, V., and Soaresa, F., (2010). Development of a Human Blood Type
  • Detection Automatic System, Procedia Engineering, 5, 496–499. Dolmashkin, A., Dubrovskii, V. A., and Zabenkov, I. V., (2012). Blood Group Typing
  • Based on Recording the Elastic Scattering of Laser Radiation Using the Method of Digital Imaging, Quantum Electronics, 42, 409-416. Swarup, D., Dhot, P. S., Kotwal, J., and Verma A. K, (2008). Comparative Study of Blood Cross Matching Using Conventional Tube and Gel Method, Medical Journal Armed Forces India, 64, 129-130. http://megadiagnostik.com.tr/page85a.html ziyaret tarihi (10.12.2013) http://www.gokselmedical.com/WEB/DIAMED.doc ziyaret tarihi (10.12.2013)
  • Gonzalez, R.C, Woods, R.E. , (2002), Digital Image Processing, Prentice-Hall, New Jersey.

JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI

Year 2013, Volume: 2 Issue: 3, 100 - 109, 01.09.2013

Güliz Toz Pakize Erdoğmuş Kadri Dönmez

Abstract

Jel kan gruplama sistemi günümüzde en çok kullanılan kan gruplama yöntemlerinden biridir. Ülkemizde de oldukça yaygın bir şekilde kullanılan bu sistemin cihaz ve kitleri hâlihazırda ithal edilmektedir. Bu çalışmada jel kan gruplama sisteminin ülkemizde üretilebilmesi amacıyla bu sistemin bir parçası olan jel test okuyucu cihazının arayüz yazılımı geliştirilmiştir. Geliştirilen yazılım kan grubu tespiti için üzerinde 6 tüp bulunan jel test numunelerini kullanmaktadır. Bu yazılım ile ilk olarak numunelerin çekilen resimleri programa aktarılmakta ve devamında sayısal görüntü işleme teknikleri ile numunenin kan grubu tespiti yapılmaktadır. Geliştirilen yazılım her biri 8 farklı kan grubundan (A Rh(+), A Rh(-), B Rh(+), B Rh(-), AB Rh(+), AB Rh(-) ve O Rh(+), O Rh(-)) birini içeren örnek jel test numuneleri kullanılarak test edilmiştir. Elde edilen sonuçlar geliştirilen yazılımın kan grubu tespitini yüksek doğruluk oranı ile gerçekleştirebildiğini göstermiştir.

Keywords

Kan grubu jel test yöntemi arayüz tasarımı.

References

  • Malomgre, W., and Neumeister, B., (2009). Recent and Future Trends in Blood Group Typing, Anal Bioanal Chem, 393, 1443-1451.
  • Okroi, M., and Mccarthy, L. J., (2010). The Original Blood Group Pioneers: The Hirszfelds, Transfusion Medicine Reviews, 24, 244-246.
  • Landsteiner, K., and Wiener, A. S., (1940). An Agglutinable Factor in Human Blood Recognized by Immune Sera for Rhesus Blood, Exp Biol Med (Maywood), 43, 223.
  • Şentuna, C., (1982). Rh Gen Frekansları Yönünden Türkiye'nin Yeri, Ankara Üniversitesi Dil ve TarihCoğrafya Fakültesi Dergisi, 30, 153-179.
  • Lapierre, Y., Rigal, D., Adam, J., Josef, D., Meyer, F., Greber, S., and Drot, C., (1990). The Gel Test: A New Way To Detect Red Cell Antigen-Antibody Reactions, Transfusion, 30, 109-113. http://megep.meb.gov.tr/mte_program_modul/moduller_pdf/Uygunluk%20Testleri.pdf
  • Kim, S. W., and Kim, N. S., (2013). Dynamic Characteristics of Suspension Bridge Hanger Cables Using Digital Image Processing, NDT & E International, 59, 25-33.
  • Adelkhani, A., Beheshti, B., Minaei, S., Javadikia, P., and Ghasemi-Varnamkhasti, M., (2013). Taste Characterization of Orange Using Image Processing Combined with ANFIS, Measurement, 46, 3573-3580.
  • Shi, Q., Ishii, H., Konno, S., Kinoshita, S., and Takanishi, A., (2012). Image Processing and Behavior Planning for RobotRat İnteraction, 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 967-973.
  • Statella, T., Pina, P., and Antônio Da Silva, E., (2012). Image Processing Algorithm for the Identification of Martian Dust Devil Tracks in MOC and HiRISE Images, Planetary and Space Science, 70, 46-58.
  • Kouloulias, V. E., Dardoufas, C. E., Kouvaris, J. R., Antypas, C. E., Sandilos, P. H., Matsopoulos, G. K., and Vlahos, L. J., (2002). Use of Image Processing Techniques to
  • Assess Effect of Disodium Pamidronate in Conjunction with Radiotherapy in Patients with Bone Metastases, Acta Oncologica, 41, 169–174. Moore, S. T., Haslwanter, T., Curthoys, I. S., and Smith, S. T., (1996). A Geometric Basis for Measurement of Three-dimensional Eye Position Using Image Processing, Vision Research, 36, 445-459.
  • Van Der Vorst, J. R., Van Dam, R. M., Van Stiphout, R. S., Van Den Broek, M. A., Hollander, I. H., Kessels, A. G., and Dejong C. H., (2010). Virtual Liver Resection and Volumetric Analysis of the Future Liver Remnant using Open Source Image Processing
  • Software, World Journal of Surgery, 34, 2426-2433.
  • Weidenbach, M., Wick, C., Pieper, S., and Redel D. A., (2000). Augmented Reality in
  • Echocardiography. A New Method of Computer-Assisted Training and Image Processing Using Virtual and Real Three-Dimensional Data Sets, Zeitschrift für Kardiologie, 89, 1681
  • Sharma, P., Nirmala, S. R., and Sarma K. K., (2013). Classification of Retinal Images Using Image Processing Techniques, Journal of Medical Imaging and Health Informatics, 3, 341-346.
  • Lin, Q., Liang, Z., Duan, C., Ma, J., Li, H., Roque, C., Yang, J., Zhang, G., Lu, H., and He, X., (2013). Motion Correction for MR Cystography by an Image Processing Approach, IEEE Transactions on Biomedical Engineering, 60, 2401-2410.
  • Şirikçi, A., Bayazit, Y. A., Kervancioğlu, S., Ozer, E., Kanlikama, M., and Bayram, M., (2004). Assessment of Mastoid Air Cell Size Versus Sigmoid Sinus Variables with a
  • Tomography-Assisted Digital Image Processing Program and Morphometry, Surgical and Radiologic Anatomy, 26, 145–148. Benetazzo, L., Bizzego, A., De Caro, R., Frigo, G., Guidolin, D., and Stecco, C., (2011). 3D Reconstruction of the Crural and Thoracolumbar Fasciae, Surgical and Radiologic Anatomy, 33, 855-862.
  • Fathima, S. M. N., (2013). Classification of Blood Types by Microscope Color Images, International Journal of Machine Learning and Computing, 3, 376-379.
  • Ferraza, A., Carvalhoa, V., and Soaresa, F., (2010). Development of a Human Blood Type
  • Detection Automatic System, Procedia Engineering, 5, 496–499. Dolmashkin, A., Dubrovskii, V. A., and Zabenkov, I. V., (2012). Blood Group Typing
  • Based on Recording the Elastic Scattering of Laser Radiation Using the Method of Digital Imaging, Quantum Electronics, 42, 409-416. Swarup, D., Dhot, P. S., Kotwal, J., and Verma A. K, (2008). Comparative Study of Blood Cross Matching Using Conventional Tube and Gel Method, Medical Journal Armed Forces India, 64, 129-130. http://megadiagnostik.com.tr/page85a.html ziyaret tarihi (10.12.2013) http://www.gokselmedical.com/WEB/DIAMED.doc ziyaret tarihi (10.12.2013)
  • Gonzalez, R.C, Woods, R.E. , (2002), Digital Image Processing, Prentice-Hall, New Jersey.
There are 24 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Güliz Toz This is me

Pakize Erdoğmuş This is me

Kadri Dönmez This is me

Publication Date September 1, 2013
Published in Issue Year 2013 Volume: 2 Issue: 3

Cite

APA Toz, G., Erdoğmuş, P., & Dönmez, K. (2013). JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI. İleri Teknoloji Bilimleri Dergisi, 2(3), 100-109.
AMA Toz G, Erdoğmuş P, Dönmez K. JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI. İleri Teknoloji Bilimleri Dergisi. September 2013;2(3):100-109.
Chicago Toz, Güliz, Pakize Erdoğmuş, and Kadri Dönmez. “JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI”. İleri Teknoloji Bilimleri Dergisi 2, no. 3 (September 2013): 100-109.
EndNote Toz G, Erdoğmuş P, Dönmez K (September 1, 2013) JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI. İleri Teknoloji Bilimleri Dergisi 2 3 100–109.
IEEE G. Toz, P. Erdoğmuş, and K. Dönmez, “JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI”, İleri Teknoloji Bilimleri Dergisi, vol. 2, no. 3, pp. 100–109, 2013.
ISNAD Toz, Güliz et al. “JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI”. İleri Teknoloji Bilimleri Dergisi 2/3 (September 2013), 100-109.
JAMA Toz G, Erdoğmuş P, Dönmez K. JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI. İleri Teknoloji Bilimleri Dergisi. 2013;2:100–109.
MLA Toz, Güliz et al. “JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI”. İleri Teknoloji Bilimleri Dergisi, vol. 2, no. 3, 2013, pp. 100-9.
Vancouver Toz G, Erdoğmuş P, Dönmez K. JEL TEST YÖNTEMİ İLE KAN GRUBU TESPİTİ İÇİN BİR YAZILIM TASARIMI. İleri Teknoloji Bilimleri Dergisi. 2013;2(3):100-9.