Araştırma Makalesi
BibTex RIS Kaynak Göster

Calculation of drug effectiveness on treatment of steatosis hepatis using HOG based ANN.

Yıl 2012, Cilt: 16 Sayı: 2, 106 - 112, 01.08.2012

Öz

-

Kaynakça

  • Gurcan, M.N, Boucheron, L.E, Can, A, Madabhushi, A, Rajpoot, N.M, Yener B,“Histopathological Image Analysis: A Review” ,In Biomedical Engineering, IEEE Reviews in Volume 2, pages 147 - 171, 2009.
  • B. Gören, T. Fen, Non-Alkolik Yaglı Karaciger Hastalıgı (Non-alcoholıc fatty liver disease: Review) Turkiye Klinikleri J Med Sci, 25:841-850, 2005.
  • Ludwig J, Viggiano TR , McGill DB, Oh BJ, Nonalcoholic steatohepatitis: Mayo Clinic experiences with a hitherto unnamed disease. Mayo Clin Proc 1980; 55(7): 434-8.
  • C. D. Byrne, R. Olufadı, K. D. Bruce,F. R. Cagampang And M. H Ahmed,Metabolic disturbances in non-alcoholic fatty liver disease. Clinical Science, 116, 539–564, 2009.
  • Matteoni CA, Younossi ZM, Gramlich T, Boparai N, Liu YC, McCullough AJ: Nonalcoholic fatty liver disease:a spectrum of clinical and pathological severity. Gastroenterology.,116(6):1413-9, 2005.
  • Brunt RM: Pathology of nonalcoholic steatohepatitis. Hepatology Research, 33, 68–71, 2005.
  • Shashua A., Gdalyahu Y., and Hayon G., “Pedestrian detection for driving assistance systems:Single-frame classification and system level performance”, In Proceedings of IEEE Intelligent Vehicles Symposium, 2004. [8] N. Dalal and B. Triggs., “Histograms of oriented gradients for human detection”, In C. Schmid, S. Soatto, and C. Tomasi, editors, International Conference on Computer Vision and Pattern Recognition, volume 2, pages 886–893, June 2005.
  • Shigeo Abe, Masahiro Kayama, Hiroshi Takenaga, Tadaaki Kitamura ,”Extracting algorithms from pattern classification neural networks” , Neural Networks, Vol: 6,Issue: 5, pp 729-735,1993.
  • Öztürk S., Sankur B., Ceyhun B., ”Karmaşalı Sahnelerde İnsan Bulunması”, In IEEE 18th Signal Processing and Communications Applications Conference (SIU), 2010.
  • Karakaya F, Altun H, Cavuslu, M.A.,”Gerçek Zamanlı Nesne Tanıma Uygulamaları için HOG Algoritmasının FPGA Tabanlı Gömülü Sistem Uyarlaması”, In IEEE 17th Signal
  • Communications ApplicationsConference(SIU), 2009.
  • SHU Chang, DING Xiaoqing, FANG Chi , “Histogram of the Oriented Gradient for Face Recognition”, Tsinghua Science & Technology,Vol:16, Issue :2, pp. 216-224 , 2011. [13] O. Déniz, G. Bueno, J. Salido, and F.D.L. Torre, "Face Recognition with Histograms of Oriented Gradients , In Proceedings of VISAPP (2), pp.339-344, 2010.
  • Yanwei Pang, Yuan Yuan, XuelongLi, JingPan, “Efficient HOG human detection”, Signal Processing,
  • Vol:91, Issue:4, pp. 773–781, 2011.
  • B. Üstündağ, İ.H.Bahçecioğlu, K. Şahin, F. Gülcü, S.Düzgün, İ.H.Özercan, M.F. Gürsu, Soy izoflavonların karbon tetraklorüre (CCLl4) bağlı karaciğer hasarı ve plazma paraoksonaz ile arilesteraz aktivite düzeylerine olan etkileri,F.Ü. Sağlık Bil. Dergisi 19(4), 263-271, 2005. and

HOG tabanlı YSA kullanılarak yağlı karaciğer tedavisindeki ilaç etkinliklerinin hesaplanması

Yıl 2012, Cilt: 16 Sayı: 2, 106 - 112, 01.08.2012

Öz

In this work, healing effects of melatonin and resveratrol drugs on liver damage in rats, induced by application of acute and chronic carbon tetrachloride (CCl4) have been examined. The study consists of three main stages: 1) Data Acquisition: 60 rats have been separated into 10 groups. Except control groups other eight groups have been injected olive oil, CCL4 (make liver fatty), CCL4+Melatonin, CCL4+Resveratrol drugs regularly and 4 and 20 days after light microscope images of rats have been obtained from liver tissue.2) Data Processing: By the help of histograms of oriented gradient (HOG) method, obtaining low-dimensional image features (color and shape) and classifying 5 different group characteristics by using these features with artificial neural networks have been provided.3) Calculation of Drug Effectiveness: Firstly to determine the differences between group characteristics of rats, a pilot group has been selected (diseased group-CCl4), and responses of artificial neural networks trained by HOG features have been calculated.As a result, it has been seen that melatonin and resveratrol drugs have %65.62 -%75.12 positive effects at the end of the fourth day, %84.12-%98.89 positive effects on healing steatosis hepatis at the end of the twentieth day respectively.

Kaynakça

  • Gurcan, M.N, Boucheron, L.E, Can, A, Madabhushi, A, Rajpoot, N.M, Yener B,“Histopathological Image Analysis: A Review” ,In Biomedical Engineering, IEEE Reviews in Volume 2, pages 147 - 171, 2009.
  • B. Gören, T. Fen, Non-Alkolik Yaglı Karaciger Hastalıgı (Non-alcoholıc fatty liver disease: Review) Turkiye Klinikleri J Med Sci, 25:841-850, 2005.
  • Ludwig J, Viggiano TR , McGill DB, Oh BJ, Nonalcoholic steatohepatitis: Mayo Clinic experiences with a hitherto unnamed disease. Mayo Clin Proc 1980; 55(7): 434-8.
  • C. D. Byrne, R. Olufadı, K. D. Bruce,F. R. Cagampang And M. H Ahmed,Metabolic disturbances in non-alcoholic fatty liver disease. Clinical Science, 116, 539–564, 2009.
  • Matteoni CA, Younossi ZM, Gramlich T, Boparai N, Liu YC, McCullough AJ: Nonalcoholic fatty liver disease:a spectrum of clinical and pathological severity. Gastroenterology.,116(6):1413-9, 2005.
  • Brunt RM: Pathology of nonalcoholic steatohepatitis. Hepatology Research, 33, 68–71, 2005.
  • Shashua A., Gdalyahu Y., and Hayon G., “Pedestrian detection for driving assistance systems:Single-frame classification and system level performance”, In Proceedings of IEEE Intelligent Vehicles Symposium, 2004. [8] N. Dalal and B. Triggs., “Histograms of oriented gradients for human detection”, In C. Schmid, S. Soatto, and C. Tomasi, editors, International Conference on Computer Vision and Pattern Recognition, volume 2, pages 886–893, June 2005.
  • Shigeo Abe, Masahiro Kayama, Hiroshi Takenaga, Tadaaki Kitamura ,”Extracting algorithms from pattern classification neural networks” , Neural Networks, Vol: 6,Issue: 5, pp 729-735,1993.
  • Öztürk S., Sankur B., Ceyhun B., ”Karmaşalı Sahnelerde İnsan Bulunması”, In IEEE 18th Signal Processing and Communications Applications Conference (SIU), 2010.
  • Karakaya F, Altun H, Cavuslu, M.A.,”Gerçek Zamanlı Nesne Tanıma Uygulamaları için HOG Algoritmasının FPGA Tabanlı Gömülü Sistem Uyarlaması”, In IEEE 17th Signal
  • Communications ApplicationsConference(SIU), 2009.
  • SHU Chang, DING Xiaoqing, FANG Chi , “Histogram of the Oriented Gradient for Face Recognition”, Tsinghua Science & Technology,Vol:16, Issue :2, pp. 216-224 , 2011. [13] O. Déniz, G. Bueno, J. Salido, and F.D.L. Torre, "Face Recognition with Histograms of Oriented Gradients , In Proceedings of VISAPP (2), pp.339-344, 2010.
  • Yanwei Pang, Yuan Yuan, XuelongLi, JingPan, “Efficient HOG human detection”, Signal Processing,
  • Vol:91, Issue:4, pp. 773–781, 2011.
  • B. Üstündağ, İ.H.Bahçecioğlu, K. Şahin, F. Gülcü, S.Düzgün, İ.H.Özercan, M.F. Gürsu, Soy izoflavonların karbon tetraklorüre (CCLl4) bağlı karaciğer hasarı ve plazma paraoksonaz ile arilesteraz aktivite düzeylerine olan etkileri,F.Ü. Sağlık Bil. Dergisi 19(4), 263-271, 2005. and
Toplam 15 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Nuh Alpaslan Bu kişi benim

Muhamed Fatih Talu Bu kişi benim

Mehmet Gül Bu kişi benim

Birgül Yiğitcan Bu kişi benim

Yayımlanma Tarihi 1 Ağustos 2012
Gönderilme Tarihi 23 Mart 2012
Kabul Tarihi 6 Ağustos 2012
Yayımlandığı Sayı Yıl 2012 Cilt: 16 Sayı: 2

Kaynak Göster

APA Alpaslan, N., Talu, M. F., Gül, M., Yiğitcan, B. (2012). HOG tabanlı YSA kullanılarak yağlı karaciğer tedavisindeki ilaç etkinliklerinin hesaplanması. Sakarya University Journal of Science, 16(2), 106-112. https://doi.org/10.16984/saufbed.13754
AMA Alpaslan N, Talu MF, Gül M, Yiğitcan B. HOG tabanlı YSA kullanılarak yağlı karaciğer tedavisindeki ilaç etkinliklerinin hesaplanması. SAUJS. Ağustos 2012;16(2):106-112. doi:10.16984/saufbed.13754
Chicago Alpaslan, Nuh, Muhamed Fatih Talu, Mehmet Gül, ve Birgül Yiğitcan. “HOG Tabanlı YSA kullanılarak yağlı karaciğer Tedavisindeki Ilaç Etkinliklerinin Hesaplanması”. Sakarya University Journal of Science 16, sy. 2 (Ağustos 2012): 106-12. https://doi.org/10.16984/saufbed.13754.
EndNote Alpaslan N, Talu MF, Gül M, Yiğitcan B (01 Ağustos 2012) HOG tabanlı YSA kullanılarak yağlı karaciğer tedavisindeki ilaç etkinliklerinin hesaplanması. Sakarya University Journal of Science 16 2 106–112.
IEEE N. Alpaslan, M. F. Talu, M. Gül, ve B. Yiğitcan, “HOG tabanlı YSA kullanılarak yağlı karaciğer tedavisindeki ilaç etkinliklerinin hesaplanması”, SAUJS, c. 16, sy. 2, ss. 106–112, 2012, doi: 10.16984/saufbed.13754.
ISNAD Alpaslan, Nuh vd. “HOG Tabanlı YSA kullanılarak yağlı karaciğer Tedavisindeki Ilaç Etkinliklerinin Hesaplanması”. Sakarya University Journal of Science 16/2 (Ağustos 2012), 106-112. https://doi.org/10.16984/saufbed.13754.
JAMA Alpaslan N, Talu MF, Gül M, Yiğitcan B. HOG tabanlı YSA kullanılarak yağlı karaciğer tedavisindeki ilaç etkinliklerinin hesaplanması. SAUJS. 2012;16:106–112.
MLA Alpaslan, Nuh vd. “HOG Tabanlı YSA kullanılarak yağlı karaciğer Tedavisindeki Ilaç Etkinliklerinin Hesaplanması”. Sakarya University Journal of Science, c. 16, sy. 2, 2012, ss. 106-12, doi:10.16984/saufbed.13754.
Vancouver Alpaslan N, Talu MF, Gül M, Yiğitcan B. HOG tabanlı YSA kullanılarak yağlı karaciğer tedavisindeki ilaç etkinliklerinin hesaplanması. SAUJS. 2012;16(2):106-12.

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