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Image-Based Computational Cardiology: From Data to Understanding

Call for Papers

Breakthroughs in imaging technologies have led to significant advances in the quality and quantity of cardiac imaging data, from cell to organ level. These developments also broaden the definition of images, which availed the observation of cardiac function in high temporal and spatial resolutions. At the same time, the power of computing facilities continues to grow worldwide over the last decade. This opens unprecedented opportunities for researchers to utilize the growing computing power to better understand and integrate multimodality cardiac imaging data, to interpret these data in the form of an in-depth understanding of the basic behaviors of the heart, to unravel the mechanisms and progression of specific heart disease patterns, and to lay down the foundation for personalized clinical care and management of heart diseases.

This special issue focuses on the relevant efforts on image-based analysis of cardiac function, covering the electrophysiological, electromechanical, and mechanical behaviors of the heart. The main goal of this special issue is to provide an overview of the current state-of-the-art advances in cardiac image computing, with a special emphasis given to the computing techniques for understanding cardiac functions and properties developed recently over the past five years. Potential topics include, but are not limited to:

  • Integrative, multiscale models to study physiological functions of the intact heart
  • Analysis and processing of widely used cardiac images (such as MRI, ultrasound, and echocardiography) and physiological recordings (such as electrocardiograms and catheter mapping data), as well as multimodal image and signal fusion methods to integrate this wide spectrum of cardiac data to assist with clinical decision-making and therapy guidance
  • Combining clinical and physiological measurements with computational models to personalize the parameters of the heart towards the personalized screening, diagnosis, therapy planning, and treatment followups
  • Optimizing computational techniques towards their clinical translations

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/acc/ according to the following timetable:

Manuscript DueFriday, 6 September 2013
First Round of ReviewsFriday, 29 November 2013
Publication DateFriday, 24 January 2014

Lead Guest Editor

  • Linwei Wang, Rochester Institute of Technology, Rochester, NY 14634, USA

Guest Editors

  • Heye Zhang, Shenzhen Institutes of Advanced Technology, Shenzhen, China
  • Vicky Wang, Auckland Bioengineering Institute, The University of Auckland, Auckland 1010, New Zealand