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

1. Front Matter

   Pages i-xii

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2. Integrating Shape and Texture in 3D Deformable Models: From Metamorphs to Active Volume Models

   • Tian Shen, Shaoting Zhang, Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas

   Pages 1-31

3. Deformable Model-Based Medical Image Segmentation

   • Gavriil Tsechpenakis

   Pages 33-67

4. Anisotropic Scale Selection, Robust Gaussian Fitting, and Pulmonary Nodule Segmentation in Chest CT Scans

   • Kazunori Okada

   Pages 69-101

5. Computerized Segmentation of Organs by Means of Geodesic Active-Contour Level-Set Algorithm

   • Kenji Suzuki

   Pages 103-128

6. Segmentation of Skin Cancer Using External Force Filtering Snake Based on Wavelet Diffusion

   • Jinshan Tang, Shengwen Guo

   Pages 129-142

7. Density and Attachment Agnostic CT Pulmonary Nodule Segmentation with Competition-Diffusion and New Morphological Operators

   • Toshiro Kubota, Anna K. Jerebko, Maneesh Dewan, Marcos Salganicoff, Arun Krishnan

   Pages 143-188

8. Accurate Modeling of Marginal Signal Distributions in 2D/3D Images

   • Ayman S. El-Baz, Georgy Gimel’farb

   Pages 189-213

9. Automated Ocular Localization in Thermographic Sequences of Contact Lens Wearer

   • Jen-Hong Tan, E. Y. K. Ng, Acharya U Rajendra, Jasjit S. Suri

   Pages 215-234

10. State-of-the-Art Medical Image Registration Methodologies: A Survey

    • Fahmi Khalifa, Garth M. Beache, Georgy Gimel’farb, Jasjit S. Suri, Ayman S. El-Baz

    Pages 235-280

11. Registered 3D Tagged MRI and Ultrasound Myocardial Elastography: Quantitative Strain Comparison

    • Zhen Qian, Wei-Ning Lee, Elisa E. Konofagou, Dimitris N. Metaxas, Leon Axel

    Pages 281-307

12. Unsupervised Change Detection in Multitemporal Images of the Human Retina

    • Giulia Troglio, Jon Atli Benediktsson, Gabriele Moser, Sebastiano Bruno Serpico, Einar Stefansson

    Pages 309-337

13. Digital Topology in Brain Image Segmentation and Registration

    • Pierre-Louis Bazin, Navid Shiee, Lotta M. Ellingsen, Jerry L. Prince, Dzung L. Pham

    Pages 339-375

14. Computer-Based Identification of Diabetic Maculopathy Stages Using Fundus Images

    • Mui Hong Ang, Acharya U Rajendra, S. Vinitha Sree, Teik-Cheng Lim, Jasjit S. Suri

    Pages 377-399

15. Back Matter

    Pages 401-410

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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.

• , Department of Bioengineering, University of Louisville, Louisville, USA

  Ayman S. El-Baz

• School of Engineering, Ngee Ann Polytechnic, Singapore, Singapore

  Rajendra Acharya U

• Bristol, United Kingdom

  Majid Mirmehdi

• Roseville, USA

  Jasjit S. Suri

Ayman S. El-Baz is currently assistant professor of Bioengineering in the Department of Bioengineering at the University of Louisville (UofL). Dr. El-Baz is an expert in the fields of bioimaging modeling and computer assisted diagnosis systems. Dr. El-Baz has extensive experience in automated detection, segmentation, and diagnosis of lung nodules in LDCT images. Dr. El-Baz received his Doctorate from University of Kentucky, Louisville, KY. Rajendra Acharya U, PhD, DEng is leader in the field of data mining and medical devices. He received two doctorates: one from National Institute of Technology Karnataka, Surathkal, India and second from Chiba University, Japan. He is a Senior IEEE member and on the editorial board of several journals. His major interests are in Signal and Image Processing, Visualization and Biophysics for better healthcare design, delivery and therapy. Currently, he is visiting faculty at Ngee Ann Polytechnic, Singapore. Majid Mirmehdi is a Professor of Computer Vision in the Computer Science Department at the University of Bristol. Prof. Mirmehdi has been involved in computer vision research for 22 years, particularly in the areas of medical imaging, quality inspection, and scene understanding. He has served as Chairman of the British Machine Vision Association, is a Senior Member of the IEEE, and was elected a Fellow of the International Association for Pattern Recognition in 2010. Dr. Jasjit S. Suri is an innovator, scientist, a visionary, an industrialist and an internationally known world leader in Biomedical Engineering. Dr. Suri has spent over 20 years in the field of biomedical engineering/devices and its management. He received his Doctrate from University of Washington, Seattle and Business Management Sciences from Weatherhead, Case Western Reserve University, Cleveland, Ohio. Dr. Suri was crowned with President’s Gold medal in 1980 and the Fellow of American Institute of Medical and Biological Engineering for his outstandingcontributions.

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