Segmentation and Classification of Abnormalities in Gallbladder - Sundari, N. Shanmuga;Kumar, L. Vinoth
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Automatic segmentation of ultrasound images is an important component of many applications domains, especially in the field of medical. Gallstone is a high incidence of gallbladder disease, Segmentation and extraction of gallstone from an ultrasound image is requirement for taking decision regarding treatment. Because of the presence of speckle noise, low contrast and luminous in-homogeneity in ultrasound images the available segmentation algorithms are general techniques. We proposed new method for the segmentation of ultrasonic images of gallstones. Segmentation, classification and level set…mehr

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Produktbeschreibung
Automatic segmentation of ultrasound images is an important component of many applications domains, especially in the field of medical. Gallstone is a high incidence of gallbladder disease, Segmentation and extraction of gallstone from an ultrasound image is requirement for taking decision regarding treatment. Because of the presence of speckle noise, low contrast and luminous in-homogeneity in ultrasound images the available segmentation algorithms are general techniques. We proposed new method for the segmentation of ultrasonic images of gallstones. Segmentation, classification and level set method as presented. A validation is required for proper identification of gallstone.
Autorenporträt
N. Shanmuga Sundari working as Assistant Professor in Velammal College of Engineering and Technology, Madurai. My area of research are Image Processing, Information Security and Image Mining. This is my first book that is related to Medical Image Processing. I want to dedicate this book to my family.