Automatic Boundary Detection and Generation of Region of Interest for Focal Liver Lesion Ultrasound Image Using Texture Analysis

The analysis of texture parameters is a useful way of increasing the information obtainable from medical images. It is an on-going field of research, with applications ranging from the segmentation of specific anatomical structures and the detection of lesions, to differentiation between pathological and healthy tissue in different organs. Finding the correct boundary in noisy images is still a difficult task. We have used GVF method for boundary detection for FLL US images. The presence of speckle noise in US images, performing the segmentation methods for the FLL images were very challenging and therefore, deleting and removing the complicated background will speed up and increases the accuracy of the segmentation process. Therefore, this study proposed an automatic ROI generation for FLL US images. Firstly, some techniques of speckle noise reduction will implemented consist of median, mean, Gaussian low-pass and Wiener filter. Then texture analysis was performed by calculating the local entropy of the image, continued with the threshold selection, morphological operations, object windowing, seed point