Medical Image Analysis

The expanded and revised edition will split Chapter 4 to include more details and examples in FMRI, DTI, and DWI for MR image modalities. The book will also expand ultrasound imaging to 3-D dynamic contrast ultrasound imaging in a separate chapter.

A new chapter on Optical Imaging Modalities elaborating microscopy, confocal microscopy, endoscopy, optical coherent tomography, fluorescence and molecular imaging will be added. Another new chapter on Simultaneous Multi-Modality Medical Imaging including CT-SPECT and CT-PET will also be added. In the image analysis part, chapters on image reconstructions and visualizations will be significantly enhanced to include, respectively, 3-D fast statistical estimation based reconstruction methods, and 3-D image fusion and visualization overlaying multi-modality imaging and information. A new chapter on Computer-Aided Diagnosis and image guided surgery, and surgical and therapeutic intervention will also be added.

A companion site containing power point slides, author biography, corrections to the first edition and images from the text can be found here: ftp://ftp.wiley.com/public/sci_tech_med/medical_image/

Send an email to: Pressbooks@ieee.org to obtain a solutions manual.  Please include your affiliation in your email.

ATAM P. DHAWAN, PhD, is Distinguished Professor in the Electrical and Computer Engineering Department at New Jersey Institute of Technology. He teaches courses in biomedical engineering and has supervised approximately fifty graduate students, including twenty-one PhD students. Dr. Dhawan is a Fellow of the IEEE and the recipient of numerous national and international awards. He has published more than 200 research articles in refereed journals, conference proceedings, and edited books. Dr. Dhawan has chaired numerous study sections and review panels for the National Institutes of Health in biomedical computing and medical imaging and health informatics. His current research interests are medical imaging, multi-modality medical image analysis, multi-grid image reconstruction, wavelets, genetic algorithms, neural networks, adaptive learning, and pattern recognition.