Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies [electronic resource] : Volume II /
El-Baz, Ayman S.editor.
Acharya U, Rajendra.editor.
Laine, Andrew F.editor.
Suri, Jasjit S.editor.
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. Ayman S. El-Baz is currently assistant professor of Bioengineering in the Department of Bioengineering at the University of Louisville (UofL).  He is an expert in the fields of bioimaging modeling and computer assisted diagnosis systems. 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. Currently, he is visiting faculty at Ngee Ann Polytechnic, Singapore. Andrew Laine is a Director of the Heffner Biomedical Imaging Laboratory in the Department of Biomedical Engineering at Columbia University in New York City and is Professor of Biomedical Engineering and Radiology (Physics).   His research interests include quantitative image analysis; cardiac functional imaging: ultrasound and MRI, retinal imaging, intravascular imaging and biosignal processing. He is a Fellow of AIMBE and IEEE. 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 Doctorate from University of Washington, Seattle and Business Management Sciences from Weatherhead, Case Western Reserve University, Cleveland, Ohio.
Description based upon print version of record.
Includes bibliographical references and index.
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.
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. Ayman S. El-Baz is currently assistant professor of Bioengineering in the Department of Bioengineering at the University of Louisville (UofL).  He is an expert in the fields of bioimaging modeling and computer assisted diagnosis systems. 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. Currently, he is visiting faculty at Ngee Ann Polytechnic, Singapore. Andrew Laine is a Director of the Heffner Biomedical Imaging Laboratory in the Department of Biomedical Engineering at Columbia University in New York City and is Professor of Biomedical Engineering and Radiology (Physics).   His research interests include quantitative image analysis; cardiac functional imaging: ultrasound and MRI, retinal imaging, intravascular imaging and biosignal processing. He is a Fellow of AIMBE and IEEE. 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 Doctorate from University of Washington, Seattle and Business Management Sciences from Weatherhead, Case Western Reserve University, Cleveland, Ohio.
Medicine.
Radiology.
Optical data processing.
Biomedical engineering.
Biomedicine, general.
Imaging / Radiology.
Image Processing and Computer Vision.
Biomedical Engineering and Bioengineering.