Main description:

With the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The central engine of any image guided surgery product is its ability to quantify the organ or segment the organ whether it is a magnetic resonance imaging (MRI) and computed tomography (CT), X-ray, PET, SPECT, Ultrasound, and Molecular imaging modality. Sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures present in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning system designs. The focus of this book in towards the state of the art techniques in the area of image segmentation and registration.

Contents:

Medical Image Segmentation: A Brief Survey.- Cerebral White Matter Segmentation using Probabilistic Graph Cut Algorithm.- A New Image-Based Framework for Analyzing Cine Images.- Medical Images Segmentation Using Learned Priors.- Classification of Breast Mass in Mammography with an Improved Level Set Segmentation by Combining Morphological Features and Texture Features.- Segmentation and Skeletonization of 3-D Contrast Enhanced Ultrasound Images for the Characterization of Single Thyroid.- Shape-Based Detection of Cortex Variability for More Accurate Discrimination Between Autistic and Normal Brains.- Surface Reconstruction and Geometric Modeling for Digital Prosthesis Design.- Medical Image Registration.- Robust Image Registration Based on Learning Prior Appearance Model.- Image Registration in Medical Imaging: Applications, Methods and Clinical Evaluation.- The Applications of Feature-Based Image Metamorphosis and Eyelashes Removal in the Investigations of Ocular Thermographic Sequences.- Segmentation-Assisted Registration for Brain MR Images.