Computers in biology and medicine
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There is no standard for measuring maximal diameter (Dmax) of abdominal aortic aneurysm (AAA) from computer tomography (CT) images although differences between Dmax evaluated from transversal (axialDmax) or orthogonal (orthoDmax) planes can be large especially for angulated AAAs. Therefore we investigated their correlations with alternative rupture risk indicators as peak wall stress (PWS) and peak wall rupture risk (PWRR) to decide which Dmax is more relevant in AAA rupture risk assessment. ⋯ It was confirmed that orthoDmax is better correlated with the alternative rupture risk predictors PWS and PWRR for angulated AAAs (DA-O≥3mm) while there is no difference between orthoDmax and axialDmax for straight AAAs (DA-O<3mm). As angulated AAAs represent a significant portion of cases it can be recommended to use orthoDmax as the only Dmax parameter for AAA rupture risk assessment.
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Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. ⋯ The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM.