Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis

1. Front Matter

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2. Acquisition Techniques

   1. Ultrasound Stimulated Vibro-acoustography

      • James F. Greenleaf, Mostafa Fatemi, Marek Belohlavek

      Pages 1-10

   2. CT from an Unmodified Standard Fluoroscopy Machine Using a Non-reproducible Path

      • Chris Baker, Chris Debrunner, Mohamed Mahfouz, William Hoff, Jamon Bowen

      Pages 11-23

   3. Three-Dimensional Object Reconstruction from Compton Scattered Gamma-Ray Data

      • Mai K. Nguyen, T. T. Truong, J. L. Delarbre, N. Kitanine

      Pages 24-34

3. Reconstruction

   1. Cone-Beam Image Reconstruction by Moving Frames

      • Xiaochun Yang, Berthold K. P. Horn

      Pages 35-47

   2. AQUATICS Reconstruction Software: The Design of a Diagnostic Tool Based on Computer Vision Algorithms

      • Andrea Giachetti, Gianluigi Zanetti

      Pages 48-63

   3. Towards Automatic Selection of the Regularization Parameters in Emission Tomgraphy by Fourier Synthesis

      • P. Maréchal, D. Mariano-Goulart, L. Giraud, S. Gratton

      Pages 64-74

4. Mathematical Methods

   1. Extraction of Myocardial Contractility Patterns from Short-Axes MR Images Using Independent Component Analysis

      • A. Suinesiaputra, A. F. Frangi, M. Üzümcü, J. H. C. Reiber, B. P. F. Lelieveldt

      Pages 75-86

   2. Principal Geodesic Analysis on Symmetric Spaces: Statistics of Diffusion Tensors

      • P. Thomas Fletcher, Sarang Joshi

      Pages 87-98

   3. Symmetric Geodesic Shape Averaging and Shape Interpolation

      • Brian Avants, James Gee

      Pages 99-110

   4. Smoothing Impulsive Noise Using Nonlinear Diffusion Filtering

      • Omer Demirkaya

      Pages 111-122

   5. Level Set and Region Based Surface Propagation for Diffusion Tensor MRI Segmentation

      • Mikaël Rousson, Christophe Lenglet, Rachid Deriche

      Pages 123-134

   6. The Beltrami Flow over Triangulated Manifolds

      • Lucero Lopez-Perez, Rachid Deriche, Nir Sochen

      Pages 135-144

   7. Hierarchical Analysis of Low-Contrast Temporal Images with Linear Scale Space

      • Tomoya Sakai, Atsushi Imiya

      Pages 145-156

5. Medical Image Segmentation

   1. Segmentation of Medical Images with a Shape and Motion Model: A Bayesian Perspective

      • Julien Sénégas, Thomas Netsch, Chris A. Cocosco, Gunnar Lund, Alexander Stork

      Pages 157-168

   2. A Multi-scale Geometric Flow for Segmenting Vasculature in MRI

      • Maxime Descoteaux, Louis Collins, Kaleem Siddiqi

      Pages 169-180

   3. A 2D Fourier Approach to Deformable Model Segmentation of 3D Medical Images

      • Eric Berg, Mohamed Mahfouz, Christian Debrunner, William Hoff

      Pages 181-192

   4. Automatic Rib Segmentation in CT Data

      • Joes Staal, Bram van Ginneken, Max A. Viergever

      Pages 193-204

   5. Efficient Initialization for Constrained Active Surfaces, Applications in 3D Medical Images

      • Roberto Ardon, Laurent D. Cohen

      Pages 205-217

   6. An Information Fusion Method for the Automatic Delineation of the Bone-Soft Tissues Interface in Ultrasound Images

      • Vincent Daanen, Jerome Tonetti, Jocelyne Troccaz

      Pages 218-229

Medical imaging and medical image analysisare rapidly developing. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to su?er from a lack of reproducibility. A signi?cant researche?ort is devoted to developing algorithms for processing the wealth of data available and extracting the relevant information in a computerized and quantitative fashion. Medical imaging and image analysis are interdisciplinary areas combining electrical, computer, and biomedical engineering; computer science; mathem- ics; physics; statistics; biology; medicine; and other ?elds. Medical imaging and computer vision, interestingly enough, have developed and continue developing somewhat independently. Nevertheless, bringing them together promises to b- e?t both of these ?elds. We were enthusiastic when the organizers of the 2004 European Conference on Computer Vision (ECCV) allowed us to organize a satellite workshop devoted to medical image analysis.

• 3 d imaging
• Computer Vision
• Image segmentation
• biomedical engineering
• biomedical image analysis
• human genome
• image analysis
• mathematical methods in computer vision
• medical image processing
• medical imaging
• mri
• statistical pattern recognition
• ultrasound imaging

• Department of Electrical and Computer Engineering, University of Iowa, Iowa City, USA

  Milan Sonka

• Computational Biomedicine Lab, University of Houston, Houston

  Ioannis A. Kakadiaris

• Center for Machine Perception, Czech Technical University, Prague 2, Czech Republic

  Jan Kybic

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