Medical volume segmentation using bank of Gabor filters
Adebayo Olowoyeye, Mihran Tüceryan, Shiaofen Fang · 2009
In this paper, we will present an unsupervised approach for segmenting medical volume images based on texture properties. The texture properties of the volume data are defined based on spatial frequencies as implemented using a statistical method known as Gabor filters. Each Gabor filter in the bank is tuned to detect patterns of a specific frequency and orientation when convolved with a medical volume. The convolution is performed in the Fourier domain and the resulting response image is a feature which is added to our feature vector. The feature vector is thus passed into a classification/segmentation algorithm.