A Hybrid Multi-Criteria Decision Making Approach for Material Selection in Biomedical Ultrasound Imaging Experiments.

doi:10.21203/rs.3.rs-4962212/v1

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Research Article

A Hybrid Multi-Criteria Decision Making Approach for Material Selection in Biomedical Ultrasound Imaging Experiments.

https://doi.org/10.21203/rs.3.rs-4962212/v1

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In this paper, we present a multi-criteria prioritization of tissue-mimicking materials for ultrasound elastography imaging experiments. A decision matrix with target-based criteria and interval data has been formed to rank the nine most suitable materials for the application based on nine target-based decision criteria. Criteria weights are calculated using the best-worst method (BWM), the entropy weight method, and the correlation of criteria weights. The existing Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is not suitable for the multi-criteria decision making (MCDM) problems in biomedical applications where target-based criteria and uncertain data are involved. Therefore, to use the TOPSIS method for such problems, the method has been modified and named the Interval data and Target criteria based TOPSIS (IT-TOPSIS) method. This IT-TOPSIS method and an extended VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method are then used to rank the materials. The study found that polyvinyl alcohol (PVA) is the best-suited soft tissue-mimicking material for ultrasound elastography imaging experiments, followed by gelatine and polyethylene glycol diacrylate (PEGDA).

Biomedical Engineering

Applied Statistics

Mechanical Engineering

Materials Engineering

Multi-criteria decision making

Ultrasound elastography

Tissue mimicking materials

Material selection.

The authors declare no competing interests.

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