Classification of Human Carcinoma Cells Using Multispectral Imagery

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Cinar U., ÇETİN Y., Cetin-Atalay R., Cetin E.

Conference on Medical Imaging - Digital Pathology, California, Amerika Birleşik Devletleri, 2 - 03 Mart 2016, cilt.9791 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 9791
  • Doi Numarası: 10.1117/12.2217022
  • Basıldığı Şehir: California
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this paper, we present a technique for automatically classifying human carcinoma cell images using textural features. An image dataset containing microscopy biopsy images from different patients for 14 distinct cancer cell line type is studied. The images are captured using a RGB camera attached to an inverted microscopy device. Texture based Gabor features are extracted from multispectral input images. SVM classifier is used to generate a descriptive model for the purpose of cell line classification. The experimental results depict satisfactory performance, and the proposed method is versatile for various microscopy magnification options.