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Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies

Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies. Ayman El-Baz, Rajendra Acharya, Majid Mirmehdi, Jasjit Suri, (eds.). Springer. March 2011. No electronic version available. External information

Abstract

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.

Content Level A> Professional/practitioner

Related subjects A> Biomedical Engineering - Biomedical Sciences - Image Processing - Radiology

Table of contents Integrating Shape and Texture in 3D Deformable Models: From Metamorphs to Active Volume Models.- Deformable Model-based Medical Image Segmentation.- Anisotropic Scale Selection, Robust Gaussian Fitting, and Pulmonary Nodule Segmentation in Chest CT Scans.- Computerized Segmentation of Organs by Means of Geodesic Active-Contour Level-Set Algorithm.- Segmentation of Skin Cancer Using External Force Filtering Snake Based on Wavelet Diffusion.- Density and Attachment Agnostic CT pulmonary Nodule Segmentation with Competition-diffusion and New Morphological Operators.- Accurate Modeling of Marginal Signal Distributions In 2d/3d Images.- Automated Ocular Localization in Thermographic Sequences of Contact Lens Wearer.- State-of-the-Art Medical Images Registration Methodologies: A Survey.- Registered 3D Tagged MRI and Ultrasound Myocardial Elastography: Quantitative Strain Comparison.- Unsupervised Change Detection in Multitemporal Images of the Human Retina.- Digital Topology in Brain Image Segmentation and Registration.- Computer-Based Identification of Diabetic Maculopathy Stages Using Fundus Images.

http://www.springer.com/biomed/book/978-1-4419-8194-3

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