Medical Image Analysis

Description

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.

Features:

• New chapter on Optical Imaging Modalities elaborating microscopy, confocal microscopy, endoscopy, optical coherent tomography, fluorescence and molecular imaging
• New chapter on Simultaneous Multi-Modality Medical Imaging including CT-SPECT and CT-PET
• 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
• New chapter on Computer-Aided Diagnosis and image guided surgery, and surgical and therapeutic intervention

Table of Contents

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.

2. Image Formation.

• 2.1 Image Coordinate System.
• 2.2 Linear Systems.
• 2.3 Point Sources 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.

3. Interaction of Electromagnetic Radiation with Matter in Medical Imaging.

• 3.1 Electromagnetic (EM) Radiation.
• 3.2 EM 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.

4. X-Ray Imaging.

• 4.1 X-Rays Imaging.
• 4.2 X-Ray Generation.
• 4.3 X-Ray 2-D Projection Imaging.
• 4.4 X-Ray Mammography.
• 4.5 X-Ray Computed Tomography.
• 4.6 Spiral X-Ray CT.
• 4.7 Contrast, Spatial Resolution and SNR.
• 4.8 Exercises.
• 4.9 References.

5. Magnetic Resonance Imaging.

• 5.1 MRI Principles.
• 5.2 MR Instrumentation.
• 5.3 MR Pulse Sequences.
• 5.4 Flow Imaging.
• 5.5 Functional MR Imaging (fMRI).
• 5.6 Diffusion Imaging.
• 5.7 Exercises.
• 5.8 References.

6. Nuclear Medicine Imaging Modalities.

• 6.1 Radioactivity.
• 6.2 Single Photon Emission Computed Tomography.
• 6.3 Positron Emission Tomography.
• 6.4 Dual Modality SPECT-CT and PET-CT Scanners.
• 6.5 Exercises.
• 6.6 References.

7. Ultrasound Imaging.

• 7.1 Propagation of Sound in a Medium.
• 7.2 Reflection and Refraction.
• 7.3 Transmission of Ultrasound Waves in a Multi-Layered 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.

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.

9. Image Processing and Enhancement.

• 9.1 Spatial Domain Methods.
• 9.2 Frequency Domain Filtering.
• 9.3 Wavelet Transform fro Image Processing.
• 9.4 Exercise.
• 9.5 References.

10. Image Segmentation.

• 10.1 Edge-Based Image Segmentation.
• 10.2 Pixel-Based Direct Classification Methods.
• 10.3 Region-based Segmentation.
• 10.4 Advanced Segmentation Methods.
• 10.5 Exercises.
• 10.8 References.

11. Image Representation and Classification Analysis.

• 11.1 Feature Extraction and Representation.
• 11.2 Feature Selection for Classification.
• 11.3 Feature and Image Classification.
• 11.4 Image Analysis Example: Analysis of “Difficult-To-Diagnose” Mammographic Microcalcifications.
• 11.5 Exercises.
• 11.6 References.

12. Image Registration.

• 12.1 Rigid-Body Transformation.
• 12.2 Principal Axes Registration.
• 12.3 Iterative Principal Axes Registration.
• 12.4 Elastic Deformation Based Registration.
• 12.5 Exercises.
• 12.6 References.

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 Virtual Reality Based Interactive Visualization.
• 13.5 Exercises.
• 13.6 References.

14. Current and Future Trends in Medical Imaging and Image Analysis.

• 14.1 Multi-Parameter Medical Imaging and Analysis.
• 14.2 Targeted Imaging.
• 14.3 Optical Imaging and Other Emerging Modalities.
• 14.4 Model-Based and Multi-Scale Analysis.
• 14.5 References.

Author Information

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.