Classification of Image Processing Software Tools for Cardiovascular Image Analysis

Abstract

Cardiovascular disease (CVD) is one of the leading causes of death in the modern world. Cardiac image analysis data is crucial in biomedical modelling and simulation to predict and diagnose CVD. Despite the importance of cardiovascular image analysis (CVIA) software tools for prediction, diagnosis, and therapy of CVD, to the best of our knowledge, there is no comprehensive review and a classification framework for the CVIA tools. In this paper, we review the literature related to the application of software tools for CVIA. In order to determine how image processing software tools are used for the CVIA diagnosis and prediction, this paper reviews the applications and features of these tools, through a survey of literature and the classification of articles, from January 2005 to December 2014. Keyword indices and article abstracts were used to identify 86 articles concerning image processing software tools for the CVIA. In this research, we review and classify 66 identified software tools for CVIA, with respect to the following four areas: (1) supported cardiovascular application, (2) cardiovascular imaging dimensionality, (3) cardiovascular imaging modality, and (4) post-processing ability. The results of our review and classification provide guidelines for utilization of CVIA software tool and future research on them.