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Computer Vision Approaches to Medical Image Analysis

Second International ECCV Workshop, CVAMIA 2006, Graz, Austria, May 12, 2006, Revised Papers

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  • © 2006
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Editors:
  1. Reinhard R. Beichel

    1. Dept. of Electrical & Computer Engineering and Dept. of Internal Medicine, The University of Iowa, USA

  2. Milan Sonka

    1. Department of Electrical and Computer Engineering, University of Iowa, Iowa City, USA

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4241)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

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Conference proceedings info: CVAMIA 2006.

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About this book

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 (22 papers)

  1. Front Matter

    Download chapter PDF

  2. Clinical Applications

    1. Melanoma Recognition Using Representative and Discriminative Kernel Classifiers

      • Tatiana Tommasi, Elisabetta La Torre, Barbara Caputo
      Pages 1-12

    2. Detection of Connective Tissue Disorders from 3D Aortic MR Images Using Independent Component Analysis

      • Michael Sass Hansen, Fei Zhao, Honghai Zhang, Nicholas E. Walker, Andreas Wahle, Thomas Scholz et al.
      Pages 13-24

    3. Comparing Ensembles of Learners: Detecting Prostate Cancer from High Resolution MRI

      • Anant Madabhushi, Jianbo Shi, Michael Feldman, Mark Rosen, John Tomaszewski
      Pages 25-36

    4. Accurate Measurement of Cartilage Morphology Using a 3D Laser Scanner

      • Nhon H. Trinh, Jonathan Lester, Braden C. Fleming, Glenn Tung, Benjamin B. Kimia
      Pages 37-48

  3. Image Registration

    1. Quantification of Growth and Motion Using Non-rigid Registration

      • D. Rueckert, R. Chandrashekara, P. Aljabar, K. K. Bhatia, J. P. Boardman, L. Srinivasan et al.
      Pages 49-60

    2. Image Registration Accuracy Estimation Without Ground Truth Using Bootstrap

      • Jan Kybic, Daniel Smutek
      Pages 61-72

    3. SIFT and Shape Context for Feature-Based Nonlinear Registration of Thoracic CT Images

      • Martin Urschler, Joachim Bauer, Hendrik Ditt, Horst Bischof
      Pages 73-84

    4. Consistent and Elastic Registration of Histological Sections Using Vector-Spline Regularization

      • Ignacio Arganda-Carreras, Carlos O. S. Sorzano, Roberto Marabini, José María Carazo, Carlos Ortiz-de-Solorzano, Jan Kybic
      Pages 85-95

  4. Image Segmentation and Analysis

    1. Comparative Analysis of Kernel Methods for Statistical Shape Learning

      • Yogesh Rathi, Samuel Dambreville, Allen Tannenbaum
      Pages 96-107

    2. Segmentation of Dynamic Emission Tomography Data in Projection Space

      • Evgeny Krestyannikov, Jussi Tohka, Ulla Ruotsalainen
      Pages 108-119

    3. A Framework for Unsupervised Segmentation of Multi-modal Medical Images

      • Ayman El-Baz, Aly Farag, Asem Ali, Georgy Gimel’farb, Manuel Casanova
      Pages 120-131

  5. Poster Session

    1. An Integrated Algorithm for MRI Brain Images Segmentation

      • Yinghua Lu, Jianzhong Wang, Jun Kong, Baoxue Zhang, Jingdan Zhang
      Pages 132-142

    2. Spatial Intensity Correction of Fluorescent Confocal Laser Scanning Microscope Images

      • Sang-Chul Lee, Peter Bajcsy
      Pages 143-154

    3. Quasi-conformal Flat Representation of Triangulated Surfaces for Computerized Tomography

      • Eli Appleboim, Emil Saucan, Yehoshua Y. Zeevi
      Pages 155-165

    4. Bony Structure Suppression in Chest Radiographs

      • M. Loog, B. van Ginneken
      Pages 166-177

    5. A Minimally-Interactive Watershed Algorithm Designed for Efficient CTA Bone Removal

      • Horst K. Hahn, Markus T. Wenzel, Olaf Konrad-Verse, Heinz-Otto Peitgen
      Pages 178-189

    6. Automatic Reconstruction of Dendrite Morphology from Optical Section Stacks

      • S. Urban, S. M. O’Malley, B. Walsh, A. Santamaría-Pang, P. Saggau, C. Colbert et al.
      Pages 190-201

    7. Modeling the Activity Pattern of the Constellation of Cardiac Chambers in Echocardiogram Videos

      • Shahram Ebadollahi, Shih-Fu Chang, Henry Wu
      Pages 202-213

    8. A Study on the Influence of Image Dynamics and Noise on the JPEG 2000 Compression Performance for Medical Images

      • Peter Michael Goebel, Ahmed Nabil Belbachir, Michael Truppe
      Pages 214-224
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  1. Computer Vision Approaches to Medical Image Analysis

Editors and Affiliations

  • Dept. of Electrical & Computer Engineering and Dept. of Internal Medicine, The University of Iowa, USA

    Reinhard R. Beichel

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

    Milan Sonka

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