Computer Vision Approaches to Medical Image Analysis: Second International ECCV Workshop, CVAMIA 2006 Graz, Austria, May 12, 2006 Revised Papers

Tatiana Tommasi, Elisabetta La Torre, Barbara Caputo (auth.), Reinhard R. Beichel, Milan Sonka (eds.)9783540462576, 3540462570

Medical imaging and medical image analysis are developing rapidly. 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. This was the second time that a satellite workshop,solely devoted to medical image analysis issues, was held in conjunction with the European Conference on Computer Vision (ECCV), and we are optimistic that this will become a tradition at ECCV. We received 38 full-length paper submissions to the second Computer Vision Approaches to Medical Image Analysis (CVAMIA) Workshop, out of which 10 were accepted for oral and 11 for poster presentation after a rigorous peer-review process. In addition, the workshop included three invited talks. The ?rst was given by Maryellen Giger from the University of Chicago, USA — titled “Multi-Modality Breast CADx”.

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Table of contents :
Front Matter….Pages –
Melanoma Recognition Using Representative and Discriminative Kernel Classifiers….Pages 1-12
Detection of Connective Tissue Disorders from 3D Aortic MR Images Using Independent Component Analysis….Pages 13-24
Comparing Ensembles of Learners: Detecting Prostate Cancer from High Resolution MRI….Pages 25-36
Accurate Measurement of Cartilage Morphology Using a 3D Laser Scanner….Pages 37-48
Quantification of Growth and Motion Using Non-rigid Registration….Pages 49-60
Image Registration Accuracy Estimation Without Ground Truth Using Bootstrap….Pages 61-72
SIFT and Shape Context for Feature-Based Nonlinear Registration of Thoracic CT Images….Pages 73-84
Consistent and Elastic Registration of Histological Sections Using Vector-Spline Regularization….Pages 85-95
Comparative Analysis of Kernel Methods for Statistical Shape Learning….Pages 96-107
Segmentation of Dynamic Emission Tomography Data in Projection Space….Pages 108-119
A Framework for Unsupervised Segmentation of Multi-modal Medical Images….Pages 120-131
An Integrated Algorithm for MRI Brain Images Segmentation….Pages 132-142
Spatial Intensity Correction of Fluorescent Confocal Laser Scanning Microscope Images….Pages 143-154
Quasi-conformal Flat Representation of Triangulated Surfaces for Computerized Tomography….Pages 155-165
Bony Structure Suppression in Chest Radiographs….Pages 166-177
A Minimally-Interactive Watershed Algorithm Designed for Efficient CTA Bone Removal….Pages 178-189
Automatic Reconstruction of Dendrite Morphology from Optical Section Stacks….Pages 190-201
Modeling the Activity Pattern of the Constellation of Cardiac Chambers in Echocardiogram Videos….Pages 202-213
A Study on the Influence of Image Dynamics and Noise on the JPEG 2000 Compression Performance for Medical Images….Pages 214-224
Fast Segmentation of the Mitral Valve Leaflet in Echocardiography….Pages 225-235
Three Dimensional Tissue Classifications in MR Brain Images….Pages 236-247
3-D Ultrasound Probe Calibration for Computer-Guided Diagnosis and Therapy….Pages 248-259
Back Matter….Pages –