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Aims & Scope

In last decades the research related with object modeling has been a source of hard work in several distinct areas of science, such as mechanical, physics, informatics and mathematics.

One major application of object modeling is in medical area. For instance, it is possible to consider the use of statistical or physical procedures on medical images in order to model the represented objects. Its modeling can have different goals: 3D shape reconstruction, object segmentation in 3D or 2D images, data interpolation, data registration, data compression, simulation, temporal tracking, motion and deformation analysis, virtual reality, computer-assisted therapy and therapy planning, tissue characterization, etc.

The main goal of the ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing consists in the provision of a comprehensive forum for discussion on the current state-of-the-art in the these fields. The Conference will enable (but is not limited to):

  • Image Processing and Analysis
  • Computer Vision
  • Processing and Analysis of Medical Images
  • Tracking and Analyze Objects in Medicine
  • Deformable Objects in Medical Images
  • Segmentation of Objects in 2D/3D Images
  • 3D Reconstruction from Medical Images
  • Application of Rapid Prototyping in Medicine
  • Signal Processing in Medicine
  • Data Interpolation, Registration, Acquisition and Compression in Medicine
  • Objects Simulation in Medicine
  • Virtual Reality in Medicine
  • Computer Aided Diagnosis, Surgery, Therapy, and Treatment
  • Computational Bioimaging and Visualization
  • Software Development for Medical Imaging
  • Telemedicine Systems and their Applications

The Conference will bring together several researchers from around the world representing several fields of study related to Computational Vision and Medical Image Processing. The expertise will span a broad range of techniques, such as finite element method, meshless methods, modal analyses, stochastic methods, principal and independent components analyses and distribution models.

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