Content Based Medical Image Classification Using Discrete Wavelet and Cosine Transforms

Karhan Z., ERGEN B.

23nd Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 16 - 19 May 2015, pp.1445-1448 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2015.7130115
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.1445-1448
  • Keywords: Medical image classification, Discrete wavelet transform (DWT), Discrete cosine transform (DCT), K-nearest neighbor algorithm
  • Ondokuz Mayıs University Affiliated: Yes


In this study, we aimed to determine whether the medical image belongs to that class or not, using the textural features of medical images. The study was performed on the images in IRMA (Image Retrieval in Medical Applications), the international database. After performing pre process on the our current medical images, discrete wavelet transform (DWT) was applied and then discrete cosine transform (DCT) was applied to each band components. After feature extraction, using of 1%, 3%, 5% and 7% of the obtained data were classified. K-Nearest neighbor algorithm (KNN) was used in the classification phase. The classificaiton performance was around 87%.