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NORMAL VE KANSERLİ HÜCRE ÇEKİRDEKLERİNİN DALGACIK DÖNÜŞÜM YÖNTEMİ İLE SINIFLANDIRILMASI

CLASSIFICATION OF NORMAL AND CANCEROUS NUCLEI BY WAVELET TRANSFORM

Journal Name:

  • Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi

Publication Year:

  • 2003

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
Nucleus images of prostate cells, acquired using a microscope, camera, and a digitizing board, are mathematically modeled by stationary wavelet transform. Daubechies, Coiflet, biorthogonal, and symmetric spline wavelets with different orders are used for the transforms. Feature vectors are calculated from the energy, entropy, and mean deviation representations of each channel output. The performance of the wavelet signatures is measured by using linear discriminant classifier. From the cross-validated classification results, it is demonstrated that mean deviation signatures calculated from the biorthogonal wavelet transform gave the best result.
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Abstract (Original Language): 
Bu çalışmada, mikroskop, kamera ve sayısallaştırıcı kart kullanılarak elde edilmiş olan prostat hücre çekirdek imgeleri, durağan dalgacık dönüşüm yöntemi kullanılarak modellenmiştir. İşlemlerde Daubechies, Coiflet, çiftdikgen ve simetrik dalgacıkların değişik tipleri kullanılmıştır. Öznitelik vektörleri, her kanal için enerji, entropi ve ortalama sapma hesaplanarak oluşturulmuştur. Modelin başarımını ölçmek için, doğrusal ayırtaç sınıflandırıcı kullanılmıştır. Çapraz sağlama yöntemi ile elde edilen sınıflandırma sonuçlarına bakıldığında, çiftdikgen dalgacık dönüşümünden elde edilen ortalama sapma özniteliklerinin en iyi sonucu verdiği görülmüştür.
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  • Turkish

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