Thus, there is a need for feature selection. To do that, a subset of the computed parameters can be selected manually. MaZda also offers the possibility of selecting the best 10 features automatically following two different selection criteria. One criterion maximizes the ratio of between-class to within-class variance, which resembles Inhibitors,research,lifescience,medical the Fisher coefficient.32,33 TTic second minimizes a combined measure of probability of classification error and correlation between features.33 The selected best 10 parameters can be used for texture classification.

Still, it is too difficult for a human operator to imagine and understand relationships between parameter http://www.selleckchem.com/products/nlg919.html vectors in the 10-dimensional data space. The B11 program of the MaZda package allows further Inhibitors,research,lifescience,medical data processing to transform them to a new, lower-dimension data space. The data preprocessing employs linear transforms,

such as principal component, analysis (PCA)34 and linear discriminant analysis (LDA),32 as well as nonlinear operations leading to artificial neural network (ANN)-based nonlinear Inhibitors,research,lifescience,medical discriminant analysis (NDA).35The B11 program displays both input and transformed data in a form of a scatter-plot graph. B11 allows also raw and transformed data vectors classification, and evaluation of the usefulness of texture features calculated using MaZda to classification of different texture classes present in image regions. For data classification, the nearest-neighbor classifier (k-NN)36 and ANN classifiers33,37,38 are implemented. Neural networks of the architecture defined during training can be tested using data sets composed of Inhibitors,research,lifescience,medical feature vectors calculated for images not used for the training. At the time of writing this paper, MaZda version 3.20 Inhibitors,research,lifescience,medical was available. It implements procedures which allow4: Loading image files in most popular MRI scanner standards

(such as Siemens, Picker, Brucker, and others). MaZda can also load images in the form of Windows Bitmap files, DICOM files, and unformatted gray-scale image files (raw images) with pixel intensity encoded with 8 or 16 bits. Additionally, details of image acquisition protocol can be extracted from the image information header. Image normalization. .There are three options: default (analysis is made for original image); ±3σ (image mean m value and standard deviation a is computed, then analysis is performed for gray scale range between m-3σ and m+3σ); or 1 % -99 % (gray-scale see more range between 1% and 99% of cumulated image histogram is taken into consideration during analysis). Definition of ROIs. The analysis is performed within these regions. Up to 16 regions of any shape can be defined; they can be also edited, loaded, and saved as disk files. A histogram of defined ROIs may be visualized and stored. Image analysis, which is computation of texture feature values within defined ROIs.