Segmentation of heart by using Gabor filter and principal component analysis

Segmentation of the heart across a cardiac cycle is a problem of interest because the left ventricle´s proper function, pumping oxygenated blood to the entire body, is vital for normal human activity. Having segmentations of the heart over time allows cardiologists to assess the dynamic behavior of the human heart (using, e.g., the ejection fraction). Segmented heart boundaries can also be useful for further quantitative analysis. Texture features has been widely used in object recognition, image analysis and many others. Gabor filter has emerged as one of the most popular ones. Gabor filter based feature extractor is a Gabor filter defined by its parameters including frequencies, orientations and smooth parameters of Gaussian envelope. Snakes have been used extensively in locating object boundaries. However, in the medical imaging field, many organs in close proximity have similar intensity values, limiting the usefulness of snakes in segmentation of abdominal organs. The gradient vector flow snake is used to test the benefits of running snakes on texture features from orientation based Gabor Filter. A proposed algorithm is GVF (gradient vector Flow) with ASM (Active Shape Model) to overcome several drawbacks in the original framework. The algorithm is completely automatic and computationally efficient.