Effect of Slice Thickness on Texture-Based Classification of Liver Dynamic CT Scans

Part 3: Biometrics and Biometrics ApplicationsInternational audienceThis paper assesses the impact of slice thickness on texture parameters. Experiments are performed on liver dynamic CT scans, with two slice thicknesses. Three acquisition moments are considered: without contrast, in arterial and in portal phase. In total, 155 texture parameters, extracted with 9 methods, are tested. Classification of normal and cirrhotic liver is performed using a boosting algorithm. Experiments reveal that slice thickness does not considerably influence the stability of the parameters. They also enable to assess the rate of parameter dependency on slice thickness. Finally, they show that applying different slice thicknesses for training and testing the CAD system requires slice thickness-independent parameters

Brain White Matter Lesions Classification in Multiple Sclerosis Subjects for the Prognosis of Future Disability

This study investigates the application of classification methods for the prognosis of future disability on MRI-detectable brain white matter lesions in subjects diagnosed with clinical isolated syndrome (CIS) of multiple sclerosis (MS). For this purpose, MS lesions and normal appearing white matter (NAWM) from 30 symptomatic untreated MS subjects, as well as normal white matter (NWM) from 20 healthy volunteers, were manually segmented, by an experienced MS neurologist, on transverse T2-weighted images obtained from serial brain MR imaging scans. A support vector machines classifier (SVM) based on texture features was developed to classify MRI lesions detected at the onset of the disease into two classes, those belonging to patients with EDSS≤2 and EDSS>2 (expanded disability status scale (EDSS) that was measured at 24 months after the onset of the disease). The highest percentage of correct classification’s score achieved was 77%. The findings of this study provide evidence that texture features of MRI-detectable brain white matter lesions may have an additional potential role in the clinical evaluation of MRI images in MS. However, a larger scale study is needed to establish the application of texture analysis in clinical practice