Pranav Bhagirath

50 Chapter 3 Implementation: A number of image processing techniques were employed. In the first stage, an Otsu-based thresholding was used. Here the threshold between healthy and scar tissue was computed by maximizing the intensity variance between the two labels in the intensity histogram (Otsu, 1975). However, as this method was subject to limitations, especially in instances where healthy and scar tissues had overlapping intensities, further steps were necessary. An ensuing connected-component analysis found groups of connected pixels. On these pixel groups, several features relevant to scar were extracted: area, bounding box, major and minor axes, eccentricity, convex- hull area and Euler number (Teague, 1980). This allowed pixel groups to be mapped to a feature space. Several classifiers were tested on the training data provided. These were namely SVM, K-nearest neighbors, linear Bayesian discriminant, and linear perceptron classifiers. SVMwas chosen based on the best trade-off between error and sensitivity on the training data (Hearst et al., 1998). Following classification using SVM, a further level-set-method step refined the segmentations obtained (Sethian, 1999). The contours obtained from the SVM classification step were used to initialize a level-set. The level-set was constrained by the search area obtained in the initial step of the algorithm. It evolved in a speed image P (x) derived from the SVM classified pixels: The values U and L were obtained from grey-level intensity I(x) statistics of the SVM output, i.e. U = μ+ 5σ and L = μ−5σ. These parameters are in-line with the standard deviation approach for classifying scar (Karim et al., 2013). Algorithm 2: Universitat Pompeu Fabra - Region growing and morphology (UPF) Background: Region-growing is a well-known image processing technique which finds a group of connected pixels with intensity homogeneity. It is an iterative process which starts from a seed point, and the region increases in size by including neighboring pixels that fit a certain pre-defined criteria. Region-growing can subsequently leak into neighboring areas, which is an important limitation of the technique.