Using hard and soft models for classification of medical images

Methods for processing and analysis of medical images are observed. A method for recognition and classification of blood cells, based on the black-box model, is proposed. Two approaches (wavelet transformation and angle measure technique) are used for construction of feature vectors and PLS discriminant analysis is used for discrimination and classification. The method is tested on the low-quality images of blood smears and shows high level of cell type recognition.