Software Evaluation

Knowledge base:

• Features

• Non-functional Properties

Upsurge of mortality rate caused by cardiac diseases can possibly be decreased by diagnosing dysfunctions in coronary arteries. Selection of inappropriate image processing software can adversely influence the results of the heart disease diagnosis and outcome prediction. The task of selecting cardiac image software becomes complex due to difficulty in understanding the functionality, applicability, and quality of the image processing software.

In this work, we proposed a framework which incorporates fuzzy-based techniques to evaluate cardiac imaging software available in the market. The proposed framework takes into consideration several categories of image processing software criteria, essential to process cardiac images for cardiac disease analysis and outcome prediction. Fuzzy techniques used in this work regulate the software evaluation procedure by aggregating ratings by researchers, for each criterion identified against alternatives, to highlight the most appropriate software for a particular processing task. This study contributes to address problems and inaccuracy in conventional methods of selecting a cardiac image processing software for diagnosis and outcome prediction of heart diseases.

More details can be found in the following publications:

• Banaeeyan, KA Rasoul, Y. K. Chiam, Z. H. Azizul, T. K. Chiew, S. H. Ab Hamid, and T. Thasaratharajah. "Classification of Image Processing Software Tools for Cardiovascular Image Analysis." In International Conference for Innovation in Biomedical Engineering and Life Sciences, pp. 72-75. Springer Singapore, 2015. [Link] [pdf]

• Tanisha Thasa Ratha Rajah, Yin Kia Chiam, Zati Azizul. "Fuzzy-based Framework for the Selection of Image Processing Software for Diagnosis and Outcome Prediction of Cardiac Diseases". [Accepted for publication in International Conference on Computational Science and Technology, 2016]