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Advanced Computer Vision Approaches in Biomedical Image Analysis

Call for Papers

Medical imaging today is becoming one of the most important visualization and interpretation methods in biology and medicine. The past decade has witnessed a tremendous development of new powerful instruments for detecting, storing, transmitting, analyzing, and displaying images. These instruments are greatly amplifying the ability of biochemists, biologists, medical scientists, and physicians to see their objects of study and to obtain quantitative measurements to support scientific hypotheses and medical diagnoses. Noise, artifacts, and weak contrast are the cause of a decrease in image quality and make the interpretation of medical images very difficult. These sources of interference, which are of a different nature for mammograms than for ultrasound images, are responsible for the fact that conventional or traditional analysis and detection algorithms are not always successful.

The biomedical imaging scene is one of the most difficult to cope with since we have to deal not only with non-Gaussian, nonstationary, and nonlinear processes (transients, bursts, and ruptures) but also with mixtures of components interacting in a quite complicated form. Therefore, much of the research done today is geared towards improvement of the reduced quality of the available biomedical imaging material.

The aim of this special issue is to present the current state of the art in the theory of advanced computer vision approaches and applications to biomedical image analysis and modeling. We are interested in articles that explore novel problems in biomedical imaging that require advanced computer vision approaches. Potential topics include, but are not limited to:

  • Computational anatomy
  • Rigid and nonrigid image registration
  • Snake, splines, and deformable models
  • Diffusion tensor image analysis
  • Time series analysis
  • Feature extraction/selection, information-theory-related approaches, and classification
  • Functional and high-resolution magnetic resonance imaging
  • Multidimensional data visualization
  • Statistical methods/population-based analysis
  • PDE-based image analysis
  • Image fusion and multimodal image analysis
  • Dynamic textures
  • Biomedical motion analysis

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/cmmm/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/cmmm/bia/ according to the following timetable:

Manuscript DueFriday, 19 April 2013
First Round of ReviewsFriday, 12 July 2013
Publication DateFriday, 6 September 2013

Lead Guest Editor

  • Anke Meyer-Baese, Department of Scientific Computing, The Florida State University, Tallahassee, FL 32306-4120, USA

Guest Editors

  • Claudia Plant, Department of Computer Science, Ludwig Maximilians University of Munich, 80539 Munich, Germany
  • Juan Manuel Gorriz Saez, Department of Signal Theory, Telematics and Communications, Faculty of Science, University of Granada, 18071 Granada, Spain