Classification of Image Processing Software Tools for Cardiovascular Image Analysis

Banaeeyan, Rasoul; Chiam, Yin Kia; Hasan, Zati Hakim Azizul; Chiew, Thiam Kian; Hamid, Siti Hafizah Ab; Thasaratharajah, T.

doi:10.1007/978-981-10-0266-3_15

Cited by 1 publication

(2 citation statements)

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“…A list of cardiac image processing software are identified is shortlisted for selection. In our earlier work [3], we have identified a list of image processing software that are suitable candidates for diagnosing cardiac diseases.…”

Section: Fuzzy-based Software Selection Framework For Cardiac Image Pmentioning

confidence: 99%

“…Although there are many image processing software systems available for diagnosis and prediction of heart diseases, the lack of classification scheme for these software often obstructs the usage of these software amongst researchers [3]. As each image processing software possess distinctive features and functionalities, researchers face difficulties in picking the best software which can fulfill their motive of study.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy-Based Framework for the Selection of Image Processing Software for Diagnosis and Outcome Prediction of Cardiac Diseases

2018

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Upsurge of mortality rate caused by cardiac diseases can possibly be decreased by diagnosing dysfunctions in coronary arteries. Evolution of technology has increased the number of image processing software to aid researchers in analyzing risks of developing heart diseases. Although there are numerous cardiac image processing software systems available, the task of comparing and selecting the most appropriate software which fits the motive of researchers is indeed a tough process. To the extent of our knowledge, although several studies are exposed into evaluation of health care systems or generic software systems, no work has been done on evaluation and selection of image processing software for heart diseases. Selection of inappropriate image processing software can adversely affect 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 systems. Thus, an approach is presented in this study to help fill the gap on this subject; by proposing a fuzzy-based framework to assist researchers with the evaluation process. The framework proposed in this research takes into consideration both functional and non-functional criteria of image processing software for cardiac disease analysis and outcome prediction. Fuzzy logic regulates the whole procedure by aggregating ratings of researchers for each criterion against the number of alternatives using fuzzy rules, to determine the most appropriate software amongst the ones provided by researchers according to the needs of individual project. This study contributes to overcome problems and inaccuracy in conventional methods of selecting a cardiac image processing software for diagnosis and outcome prediction of heart diseases.

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Section: Fuzzy-based Software Selection Framework For Cardiac Image Pmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fuzzy-Based Framework for the Selection of Image Processing Software for Diagnosis and Outcome Prediction of Cardiac Diseases

2018

View full text Add to dashboard Cite

show abstract

Classification of Image Processing Software Tools for Cardiovascular Image Analysis

Cited by 1 publication

References 3 publications

Fuzzy-Based Framework for the Selection of Image Processing Software for Diagnosis and Outcome Prediction of Cardiac Diseases

Fuzzy-Based Framework for the Selection of Image Processing Software for Diagnosis and Outcome Prediction of Cardiac Diseases

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