Araştırma Makalesi
Yıl 2017,
Cilt: 17 Sayı: 3, 283 - 294, 01.09.2017
Öz
Monitoring of hematological values which provide important information about
the health status of fish is considerably important in aquaculture. One of the
most commonly used methods for detecting the hematological values in fish blood
is the usage of Natt-Herrick solution. Basically, in this approach, Natt-Herrick
stained blood samples are examined with a microscope and the cells are counted.
Nevertheless, the counting process is both tough and time-consuming. In this
study, a technique in which cell counting in blood samples images is
automatically performed has been presented. Natt-Herrick stained blood samples of
Oncorhynchus mykiss and Sparus aurata were used for evaluation
of the developed scheme. The outputs generated by automatic blood cells detection
algorithm in 90 images were compared with results which were obtained by means
of user’s intervention. Consequently, an
average f-score over 0.96 was achieved.
Anahtar Kelimeler
Kaynakça
- Arnold, J.E., Matsche, M.A. & Rosemary, K. (2014). Preserving whole blood in formalin extends the specimen stability period for manual cell counts for fish. Veterinary Clinical Pathology 43(4), 613–620. http://dx.doi.org/10.1111/vcp.12214
- Bai, X., Sun, C. & Zhou, F. (2009). Splitting touching cells based on concave points and ellipse fitting. Pattern Recognition 42(11), http://dx.doi.org/10.1016/j.patcog.2009.04.003
- Chetverikov, D. & Szabo, Z. (1999). A simple and efficient algorithm for detection of high curvature points in planar curves. Proceedings of the 23rd Workshop of Austrian Pattern Recognition Group. 175-184. http://dx.doi.org/10.1007/978-3-540-45179-2_91
- Demirci, R. (2010). Adaptive threshold selection for edge detection in colour images. IEEE 18nd Signal Processing and Communications Applications Conference (SIU), 677-679. http://dx.doi.org/10.1109/SIU.2010.5654414
- Fan, J., Yau, D.K.Y., Elmagarmid, A.K. & Aref, W.G. (2001). Automatic image segmentation by integrating color-edge extraction and seeded region growing. IEEE Transactions On Image Processing, 10(10), 1454-1466. http://dx.doi.org/10.1109/83.951532
- Gonçalves, W.N. & Bruno, O.M. (2012). Automatic system for counting cells with elliptical shape. Computer Vision and Pattern Recognition 9(1), 1-11. http://dx.doi.org/10.21528/LNLM-vol9-no1-art1
- Gonzalez, R.C. & Woods, R.E. (2008). Digital Image Processing, 3rd Edition. New Jersey, USA: Pearson Education Inc.
- Guyon, C., Bouwmans, T. & Zahzah, E.H. (2012). Robust principal component analysis for background subtraction: Systematic evaluation and comparative analysis. In P. Sanguansat (Eds.), Principal Component Analysis (pp. 223-237). Rijeka, Croatia: InTech.
- Halir, R. & Flusser, J. (1998). Numerically stable direct least squares fitting of ellipses. Proc. 6th International Conference in Central Europe on Computer Graphics and Visualization (WSCG). 125-132.
- İncetas, M.O., Demirci, R., Yavuzcan, H.G., Tanyeri, U. & Veske, E. (2014). Seeded region growing based detection of cells in fish blood stained with Natt-Herrick. IEEE 22nd Signal Processing and Communications Applications Conference (SIU), 1471-1474. http://dx.doi.org/10.1109/SIU.2014.6830518
- Konuk, T. (1975). Pratik Fizyoloji I. Ankara, Turkey: Ankara Üniversitesi Veteriner Fakültesi Yayınları.
- Leyk, S. & Boesch, R. (2010). Colors of the past: color image segmentation in historical topographic maps based on homogeneity. Geoinformatica, 14(1), 1–21. http://dx.doi.org/10.1007/s10707-008-0074-z
- Luskova, V. (1997). Annual cycles and normal values of hematological parameters in fishes.
- Acta Scientarum Naturalium Academiae Scientiarum Bohemicae Brno, 31(5): 70-78.
- Martin, D.R., Fowlkes, C.C. & Malik, J. (2004). Learning to detect natural image boundaries using local brightness, color and texture cues. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(5): 530-549. http://dx.doi.org/10.1109/TPAMI.2004.1273918
- Pavlidis, M., Futter, W. C., Katharios, P. & Divanach, P. (2007). Blood cell profile of six Mediterranean mariculture fish species. Journal of Applied Ichthyology, 23(1): 70-73. http://dx.doi.org/10.1111/j.1439-0426.2006.00771.x
- Qiang, J., Yang, H., Wang, H., Kpundeh, M.D. & Xu, P. (2013). Interacting effects of water temperature and dietary protein level on hematological parameters in Nile tilapia juveniles, Oreochromis niloticus (L.) and mortality under Streptococcus iniae infection. Fish & Shellfish Immunology. 34(1): 8-16. http://dx.doi.org/10.1016/j.fsi.2012.09.003
- Tavares - Dias, M. & Moraes, F. R. (2008). Haematological and biochemical reference intervals for farmed channel catfish. Journal of Fish Biology, 71(2): 383-388 http://dx.doi.org/10.1111/j.1095-8649.2007.01494.x
- Van Rijsbergen, C.J. (1979). Information Retrieval, Second Ed., London, United Kingdom: Butterworths
Yıl 2017,
Cilt: 17 Sayı: 3, 283 - 294, 01.09.2017
Öz
Hematolojik değerlerin kontrolü balıkların
sağlık durumları hakkında önemli bilgiler verdiğinden, bu kontrol balık
yetiştiriciliğinde oldukça önemlidir. Hematolojik değerlerin kontrolünde en sık
kullanılan yöntemlerden biri de Natt-Herrick solüsyonudur. Natt-Herrick
solüsyonu yardımıyla boyanan kan örnekleri mikroskop ile incelenmekte ve hücre
sayımı yapılmaktadır. Ancak bu sayım hem yorucu hem de zaman alıcıdır. Bu
çalışmada kan örneklerine ait görüntüler üzerinden otomatik olarak hücre sayımı
yapabilecek bir teknik sunulmuştur. Geliştirilen yöntemin değerlendirilmesinde
Natt-Herrick solüsyonu ile boyanmış Gökkuşağı Alabalığı ve Çipura balıklarına
ait örnekler kullanılmıştır. Bu örneklere ait 90 adet görüntüdeki kan
hücrelerinin otomatik belirlenmesi sonuçları ile kullanıcılar tarafından
belirlenen sonuçlarla karşılaştırılmıştır. Karşılaştırma sonucunda ortalama
olarak 0,96’nın üzerinde f-skor değeri elde edilmiştir.
Anahtar Kelimeler
Kaynakça
- Arnold, J.E., Matsche, M.A. & Rosemary, K. (2014). Preserving whole blood in formalin extends the specimen stability period for manual cell counts for fish. Veterinary Clinical Pathology 43(4), 613–620. http://dx.doi.org/10.1111/vcp.12214
- Bai, X., Sun, C. & Zhou, F. (2009). Splitting touching cells based on concave points and ellipse fitting. Pattern Recognition 42(11), http://dx.doi.org/10.1016/j.patcog.2009.04.003
- Chetverikov, D. & Szabo, Z. (1999). A simple and efficient algorithm for detection of high curvature points in planar curves. Proceedings of the 23rd Workshop of Austrian Pattern Recognition Group. 175-184. http://dx.doi.org/10.1007/978-3-540-45179-2_91
- Demirci, R. (2010). Adaptive threshold selection for edge detection in colour images. IEEE 18nd Signal Processing and Communications Applications Conference (SIU), 677-679. http://dx.doi.org/10.1109/SIU.2010.5654414
- Fan, J., Yau, D.K.Y., Elmagarmid, A.K. & Aref, W.G. (2001). Automatic image segmentation by integrating color-edge extraction and seeded region growing. IEEE Transactions On Image Processing, 10(10), 1454-1466. http://dx.doi.org/10.1109/83.951532
- Gonçalves, W.N. & Bruno, O.M. (2012). Automatic system for counting cells with elliptical shape. Computer Vision and Pattern Recognition 9(1), 1-11. http://dx.doi.org/10.21528/LNLM-vol9-no1-art1
- Gonzalez, R.C. & Woods, R.E. (2008). Digital Image Processing, 3rd Edition. New Jersey, USA: Pearson Education Inc.
- Guyon, C., Bouwmans, T. & Zahzah, E.H. (2012). Robust principal component analysis for background subtraction: Systematic evaluation and comparative analysis. In P. Sanguansat (Eds.), Principal Component Analysis (pp. 223-237). Rijeka, Croatia: InTech.
- Halir, R. & Flusser, J. (1998). Numerically stable direct least squares fitting of ellipses. Proc. 6th International Conference in Central Europe on Computer Graphics and Visualization (WSCG). 125-132.
- İncetas, M.O., Demirci, R., Yavuzcan, H.G., Tanyeri, U. & Veske, E. (2014). Seeded region growing based detection of cells in fish blood stained with Natt-Herrick. IEEE 22nd Signal Processing and Communications Applications Conference (SIU), 1471-1474. http://dx.doi.org/10.1109/SIU.2014.6830518
- Konuk, T. (1975). Pratik Fizyoloji I. Ankara, Turkey: Ankara Üniversitesi Veteriner Fakültesi Yayınları.
- Leyk, S. & Boesch, R. (2010). Colors of the past: color image segmentation in historical topographic maps based on homogeneity. Geoinformatica, 14(1), 1–21. http://dx.doi.org/10.1007/s10707-008-0074-z
- Luskova, V. (1997). Annual cycles and normal values of hematological parameters in fishes.
- Acta Scientarum Naturalium Academiae Scientiarum Bohemicae Brno, 31(5): 70-78.
- Martin, D.R., Fowlkes, C.C. & Malik, J. (2004). Learning to detect natural image boundaries using local brightness, color and texture cues. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(5): 530-549. http://dx.doi.org/10.1109/TPAMI.2004.1273918
- Pavlidis, M., Futter, W. C., Katharios, P. & Divanach, P. (2007). Blood cell profile of six Mediterranean mariculture fish species. Journal of Applied Ichthyology, 23(1): 70-73. http://dx.doi.org/10.1111/j.1439-0426.2006.00771.x
- Qiang, J., Yang, H., Wang, H., Kpundeh, M.D. & Xu, P. (2013). Interacting effects of water temperature and dietary protein level on hematological parameters in Nile tilapia juveniles, Oreochromis niloticus (L.) and mortality under Streptococcus iniae infection. Fish & Shellfish Immunology. 34(1): 8-16. http://dx.doi.org/10.1016/j.fsi.2012.09.003
- Tavares - Dias, M. & Moraes, F. R. (2008). Haematological and biochemical reference intervals for farmed channel catfish. Journal of Fish Biology, 71(2): 383-388 http://dx.doi.org/10.1111/j.1095-8649.2007.01494.x
- Van Rijsbergen, C.J. (1979). Information Retrieval, Second Ed., London, United Kingdom: Butterworths
Toplam 19 adet kaynakça vardır.
Ayrıntılar
| Bölüm | Araştırma Makalesi |
|---|---|
| Yazarlar | |
| Yayımlanma Tarihi | 1 Eylül 2017 |
| Yayımlandığı Sayı | Yıl 2017 Cilt: 17 Sayı: 3 |