Information Processing in Medical Imaging

1. Front Matter

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2. Shape Modelling

   1. Shape Modelling Using Markov Random Field Restoration of Point Correspondences

      • Rasmus R. Paulsen, Klaus B. Hilger

      Pages 1-12

   2. Optimal Deformable Surface Models for 3D Medical Image Analysis

      • P. Horkaew, G. Z. Yang

      Pages 13-24

   3. Learning Object Correspondences with the Observed Transport Shape Measure

      • Alain Pitiot, Hervé Delingette, Arthur W. Toga, Paul M. Thompson

      Pages 25-37

   4. Shape Discrimination in the Hippocampus Using an MDL Model

      • Rhodri H. Davies, Carole J. Twining, P. Daniel Allen, Tim F. Cootes, Christopher J. Taylor

      Pages 38-50

3. Posters I: Shape Modelling and Analysis

   1. Minimum Description Length Shape and Appearance Models

      • Hans Henrik Thodberg

      Pages 51-62

   2. Evaluation of 3D Correspondence Methods for Model Building

      • Martin A. Styner, Kumar T. Rajamani, Lutz-Peter Nolte, Gabriel Zsemlye, Gábor Székely, Christopher J. Taylor et al.

      Pages 63-75

   3. Localization of Anatomical Point Landmarks in 3D Medical Images by Fitting 3D Parametric Intensity Models

      • Stefan Wörz, Karl Rohr

      Pages 76-88

   4. Morphology-Based Cortical Thickness Estimation

      • Gabriele Lohmann, Christoph Preul, Margret Hund-Georgiadis

      Pages 89-100

   5. The Shape Operator for Differential Analysis of Images

      • Brian Avants, James Gee

      Pages 101-113

   6. Feature Selection for Shape-Based Classification of Biological Objects

      • Paul Yushkevich, Sarang Joshi, Stephen M. Pizer, John G. Csernansky, Lei E. Wang

      Pages 114-125

   7. Corresponding Articular Cartilage Thickness Measurements in the Knee Joint by Modelling the Underlying Bone (Commercial in Confidence)

      • Tomos G. Williams, Christopher J. Taylor, ZaiXiang Gao, John C. Waterton

      Pages 126-135

   8. Adapting Active Shape Models for 3D Segmentation of Tubular Structures in Medical Images

      • Marleen de Bruijne, Bram van Ginneken, Max A. Viergever, Wiro J. Niessen

      Pages 136-147

   9. A Unified Variational Approach to Denoising and Bias Correction in MR

      • Ayres Fan, William M. Wells, John W. Fisher, Müjdat Çetin, Steven Haker, Robert Mulkern et al.

      Pages 148-159

4. Shape Analysis

   1. Object-Based Strategy for Morphometry of the Cerebral Cortex

      • J. -F. Mangin, D. Rivière, A. Cachia, D. Papadopoulos-Orfanos, D. L. Collins, A. C. Evans et al.

      Pages 160-171

   2. Genus Zero Surface Conformal Mapping and Its Application to Brain Surface Mapping

      • Xianfeng Gu, Yalin Wang, Tony F. Chan, Paul M. Thompson, Shing-Tung Yau

      Pages 172-184

5. Segmentation

   1. Coupled Multi-shape Model and Mutual Information for Medical Image Segmentation

      • A. Tsai, William M. Wells, Clare Tempany, E. Grimson, Alan S. Willsky

      Pages 185-197

   2. Neighbor-Constrained Segmentation with 3D Deformable Models

      • Jing Yang, Lawrence H. Staib, James S. Duncan

      Pages 198-209

   3. Expectation Maximization Strategies for Multi-atlas Multi-label Segmentation

      • Torsten Rohlfing, Daniel B. Russakoff, Calvin R. Maurer

      Pages 210-221

   4. Quantitative Analysis of Intrathoracic Airway Trees: Methods and Validation

      • Kálmán Palágyi, Juerg Tschirren, Milan Sonka

      Pages 222-233

IPMI occupies an important position in the scienti?c calendar. Every two years, it brings together leading researchers in medical image formation, analysis and interpretation, for an international workshop that allows extensive, in-depth d- cussion of new ideas. Many of the most in?uential developments in the ?eld were ?rst presented at IPMI, and the series has done much to foster a rigorous sci- ti?c approach to information processing in medical imaging. IPMI 2003 was held over 5 days in July 2003 at St. Martin’s College, - bleside, in the heart of the English Lake District. Full papers were invited on any aspect of information processing in medical imaging, with particular - couragement for submissions exploring generic mathematical or computational principles. Recognizing the rapidly evolving nature of the ?eld, we encouraged a broadinterpretationofmedicalimaging:frommacroscopictomolecularimaging; from applications in patient care to those in biomedical research. We received 123 submissions by the deadline in February 2003. Each paper was reviewed by four members of the Scienti?c Committee, placing particular emphasis on originality, scienti?c rigor, and biomedical relevance. Papers were selected for the meeting by a Paper Selection Committee, based on reviewers’ rankings and theirdetailedcomments. Atotalof28paperswereacceptedasoralpresentations and 29 as posters. Unfortunately, the standard was so high that we had to turn down many excellent papers.

• 3D
• Bayesian inference
• Radiologieinformationssystem
• computer version
• diagnosis
• image analysis
• magnetic resonance imaging
• medical image analysis
• medical image computing
• medical image processing
• medical image sequences
• medical imaging
• mri
• radiology
• visualization

• Imaging Science and Biomedical Engineering (ISBE), University of Manchester, Manchester, UK

  Chris Taylor

• Department of Engineering Science, University of Oxford, UK

  J. Alison Noble

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