Content based medical image classification using discrete wavelet and cosine transforms - Karhan, Zehra; Ergen, Burhan (Institute of Electrical and Electronics Engineers Inc., 2015)
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 classification performance was around 87%. © 2015 IEEE.
Ayrik Dalgacik ve Kosinüs Dönüşümleri Kullanilarak Içerik Tabanli Tibbi Imgelerin Siniflandirilmasi
2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- Malatya -- 113052
Keywords: Discrete cosine transform (DCT); Discrete wavelet transform (DWT); K-nearest neighbor algorithm; Medical image classification