Medical Image Analysis

Now updated—the most comprehensive reference of medical imaging modalities and image analysis techniques
The last two decades have witnessed revolutionary advances in medical imaging and computerized medical image processing. With the advent and enhancement of numerous sophisticated medical imaging modalities, intelligent processing of multi–dimensional images has become critical in radiological and diagnostic applications.
This benchmark text takes a unique, all–inclusive approach to the topic—one that weaves together medical physics, medical imaging instrumentation, and advanced image analysis methods. This Second Edition is completely revised and expanded to provide a broader foundation, helping engineers, medical professionals, and students alike understand medical imaging principles, perform intelligent image interpretation, and navigate the intricacies of instrumentation, data collection, image reconstruction, and computerized image analysis for radiological computer–aided evaluation and diagnosis. New chapters cover:
More in–depth description of recent developments in medical imaging instrumentation, including spiral CT, diagnostic ultrasound, functional MRI, and Diffusion Tension Imaging
Simultaneous multi–modality medical imaging, including CT–SPECT and CT–PET
Advanced medical image analysis and classification methods for computer–aided diagnosis, and therapeutic intervention
This updated edition presents individual chapters focused on x–ray, MRI, nuclear medicine, and ultrasound imaging modalities with additional details and recent advances. In addition, chapters on image reconstructions and visualizations have been significantly enhanced to include, respectively, 3–D statistical estimation–based reconstruction methods, feature classification and multi–modality image visualization. Examples with clinical images for medical imag e analysis and computer–aided diagnosis are provided throughout, as well as skill–building MATLAB exercises.
An ideal learning tool, this state–of–the–art resource can be used for one– or two–semester based senior undergraduate and/or graduate–level courses. Students in medical imaging and image processing, electrical and computer engineering, computer science, and biomedical engineering as well as physicians, medical physicists, and researchers will gain the knowledge to master the complexities of today′s radiological and diagnostic applications.

Spis treści:
PREFACE TO THE SECOND EDITION.
CHAPTER 1 INTRODUCTION.
1.1. Medical Imaging: A Collaborative Paradigm.
1.2. Medical Imaging Modalities.
1.3. Medical Imaging: from Physiology to Information Processing.
1.4. General Performance Measures.
1.5. Biomedical Image Processing and Analysis.
1.6. Matlab Image Processing Toolbox.
1.7. Imagepro Interface in Matlab Environment and Image Databases.
1.8. Imagej and Other Image Processing Software Packages.
1.9. Exercises.
1.10. References.
1.11. Definitions.
CHAPTER 2 IMAGE FORMATION.
2.1. Image Coordinate System.
2.2. Linear Systems.
2.3. Point Source and Impulse Functions.
2.4. Probability and Random Variable Functions.
2.5. Image Formation.
2.6. Pin–hole Imaging.
2.7. Fourier Transform.
2.8. Radon Transform.
2.9. Sampling.
2.10. Discrete Fourier Transform.
2.11. Wavelet Transform.
2.12. Exercises.
2.13. References.
CHAPTER 3 INTERACTION OF ELECTROMAGNETIC RADIATION WITH MATTER IN MEDICAL IMAGING.
3.1. Electromagnetic Radiation.
3.2. Electromagnetic Radiation for Image Formation.
3.3. Radiation Interaction with Matter.
3.4. Linear Attenuation Coefficient.
3.5. Radiation Detection.
3.6. Detector Subsystem Output Voltage Pulse.
3.7. Exercises.
3.8. References.
CHAPTER 4 MEDICAL IMAGING MODALITIES: X–RAY IMAGING.
4.1. X–Ray Imaging.
4.2. X–Ray Generation.
4.3. X–Ray 2–D Projection Imaging.
4.4. X–Ray Mammography.
4.5. X–Ray CT.
4.6. Spiral X–Ray CT.
4.7. Contrast Agent, Spatial Resolution, and SNR.
4.8. Exercises.
4.9. References.
CHAPTER 5 MEDICAL IMAGING MODALITIES: MAGNETIC RESONANCE IMAGING.
5.1. MRI Principles.
5.2. MR Instrumentation.
5.3. MRI Pulse Sequences.
5.4. Flow Imaging.
5.5. fMRI.
5.6. Diffusion Imaging.
5.7. Contrast, Spatial Resolution, and SNR.
5.8. Exercises.
5.9. References.
CHAPTER 6 NUCLEAR MEDICINE IMAGING MODALITIES.
6.1. Radioactivity.
6.2. SPECT.
6.3. PET.
6.4. Dual–Modality Spect–CT and PET–CT Scanners.
6.5. Exercises.
6.6. References.
CHAPTER 7 MEDICAL IMAGING MODALITIES: ULTRASOUND IMAGING.
7.1. Propagation of Sound in a Medium.
7.2. Reflection and Refraction.
7.3. Transmission of Ultrasound Waves in a Multilayered Medium.
7.4. Attenuation.
7.5. Ultrasound Reflection Imaging.
7.6. Ultrasound Imaging Instrumentation.
7.7. Imaging with Ultrasound: A–Mode.
7.8. Imaging with Ultrasound: M–Mode.
7.9. Imaging with Ultrasound: B–Mode.
7.10. Doppler Ultrasound Imaging.
7.11. Contrast, Spatial Resolution, and SNR.
7.12. Exercises.
7.13. References.
CHAPTER 8 IMAGE RECONSTRUCTION.
8.1. Radon Transform and Image Reconstruction.
8.2. Iterative Algebraic Reconstruction Methods.
8.3. Estimation Methods.
8.4. Fourier Reconstruction Methods.
8.5. Image Reconstruction in Medical Imaging Modalities.
8.6. Exercises.
8.7. References.
CHAPTER 9 IMAGE PROCESSING AND ENHANCEMENT.
9.1. Spatial Domain Methods.
9.2. Frequency Domain Filtering.
9.3. Wavelet Transform for Image Processing.
9.4. Exercises.
9.5. References.
CHAPTER 10 IM AGE SEGMENTATION.
10.1. Edge–Based Image Segmentation.
10.2. Pixel–Based Direct Classifi cation Methods.
10.3. Region–Based Segmentation.
10.4. Advanced Segmentation Methods.
10.5. Exercises.
10.6. References.
CHAPTER 11 IMAGE REPRESENTATION, ANALYSIS, AND CLASSIFICATION.
11.1. Feature Extraction and Representation.
11.2. Feature Selection for Classification.
11.3. Feature and Image Classification.
11.4. Image Analysis and Classification Example: "Difficult–To–Diagnose" Mammographic Microcalcifications.
11.5. Exercises.
11.6. References.
CHAPTER 12 IMAGE REGISTRATION.
12.1. Rigid–Body Transformation.
12.2. Principal Axes Registration.
12.3. Iterative Principal Axes Registration.
12.4. Image Landmarks and Features–Based Registration.
12.5. Elastic Deformation–Based Registration.
12.6. Exercises.
12.7. References.
CHAPTER 13 IMAGE VISUALIZATION.
13.1. Feature–Enhanced 2–D Image Display Methods.
13.2. Stereo Vision and Semi–3–D Display Methods.
13.3. Surface– and Volume–Based 3–D Display Methods.
13.4. VR–Based Interactive Visualization.
13.5. Exercises.
13.6. References.
CHAPTER 14 CURRENT AND FUTURE TRENDS IN MEDICAL IMAGING AND IMAGE ANALYSIS.
14.1. Multiparameter Medical Imaging and Analysis.
14.2. Targeted Imaging.
14.3. Optical Imaging and Other Emerging Modalities.
14.4. Model–Based and Multiscale Analysis.
14.5. References.
INDEX.

Nota biograficzna:
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.

Okładka tylna:
Now updated—the most comprehensive reference of medical imaging modalities and image analysis techniques
The last two decades have witnessed revolutionary advances in medical imaging and computerized medical image processing. With the advent and enhancement of numerous sophisticated medical imaging modalities, intelligent processing of multi–dimensional images has become critical in radiological and diagnostic applications.
This benchmark text takes a unique, all–inclusive approach to the topic—one that weaves together medical physics, medical imaging instrumentation, and advanced image analysis methods. This Second Edition is completely revised and expanded to provide a broader foundation, helping engineers, medical professionals, and students alike understand medical imaging principles, perform intelligent image interpretation, and navigate the intricacies of instrumentation, data collection, image reconstruction, and computerized image analysis for radiological computer–aided evaluation and diagnosis. New chapters cover:
More in–depth description of recent developments in medical imaging instrumentation, including spiral CT, diagnostic ultrasound, functional MRI, and Diffusion Tension Imaging
Simultaneous multi–modality medical imaging, including CT–SPECT and CT–PET
Advanced medical image analysis and classif ication methods for computer–aided diagnosis, and therapeutic intervention
This updated edition presents individual chapters focused on x–ray, MRI, nuclear medicine, and ultrasound imaging modalities with additional details and recent advances. In addition, chapters on image reconstructions and visualizations have been significantly enhanced to include, respectively, 3–D statistical estimation–based reconstruction methods, feature classification and multi–modality image visualization. Examples with clinical images for medical image analysis and computer–aided diagnosis are provided throughout, as well as skill–building MATLAB exercises.
An ideal learning tool, this state–of–the–art resource can be used for one– or two–semester based senior undergraduate and/or graduate–level courses. Students in medical imaging and image processing, electrical and computer engineering, computer science, and biomedical engineering as well as physicians, medical physicists, and researchers will gain the knowledge to master the complexities of today′s radiological and diagnostic applications.