Medical Imaging and Augmented Reality 医学成像和现实

This book constitutes the refereed proceedings of the Second International Workshop on Medical Imaging and Augmented Reality, MIAR 2004, held in Beijing, China, in August 2004.
The 41 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 93 submissions. The papers are organized in topical sections on image processing, reconstruction, and coding; statistical and shape based segmentation; brain image analysis; cardiac modeling and segmentation; image registration; and surgical navigation and augmented reality.

Invited Contributions
New Advances in MRI
Segmentation of Focal Brain Lesions
Imaging Support of Minimally Invasive Procedures
Hands-On Robotic Surgery: Is This the Future?
Image Processing, Reconstruction and Coding
An Adaptive Enhancement Method for Ultrasound Images
State Space Strategies for Estimation of Activity Map in PET Imaging
Applying ICA Mixture Analysis for Segmenting Liver from Multi-phase Abdominal CT Images
Extracting Pathologic Patterns from NIR Breast Images with Digital Image Processing Techniques
Comparison of Phase-Encoded and Sensitivity-Encoded Spectroscopic Imaging
Detection and Restoration of a Tampered Medical Image
Efficient Lossy to Lossless Medical Image Compression Using Integer Wavelet Transform and Multiple Subband Decomposition
Statistical and Shape Based Segmentation
Geodesic Active Regions Using Non-parametric Statistical Regional Description and Their Application to Aneurysm Segmentation from CTA
An Efficient Method for Deformable Segmentation of 3D US Prostate Images
White Matter Lesion Segmentation from Volumetric MR Images
Active Shape Model Segmentation Using Local Edge Structures and AdaBoost
Segmental Active Contour Model Integrating Region Information for Medical Image Segmentation
A Level Set Algorithm for Contour Tracking in Medical Images
Robust Object Segmentation with Constrained Curve Embedding Potential Field
Tracking Lumbar Vertebrae in Digital Videofluoroscopic Video Automatically
Brain Image Analysis
A New Algorithm Based on Fuzzy Gibbs Random Fields for Image Segmentation
Improved Fiber Tracking for Diffusion Tensor MRI
Rapid and Automatic Exttraction of the Modified Talairach Cortical Landmarks from MR Neuroimages
Brain MR Image Segmentation Using Fuzzy Clustering With Spatial Constraints Based on Markov Random Field Theory
……
Cardiac Modeling and Segmentation
Image Registration
Surgical Navigation and Augmented Reality
Author Index