In this paper, a new technique is proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. The technique uses a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The classifica...

in order to study the effects of magnetic field, silver nano particles and micronutrient fertilizers on sugar beet, an experiment was conducted at razavi research and technology institute, mashhad, iran. experiment carried out with seven treatments based on randomized complete block design with three replications. treatments included (t1) magnetic field and silver nano particles + kemira fertil...

The impact of the magnetic field on postbounce supernova dynamics non-rotating stellar cores is studied by performing three-dimensional magnetohydrodynamics simulations with spectral neutrino transport. explodability strongly and weakly magnetized models $20$ $27$ $M_{\odot}$ pre-supernova progenitors are compared. We find that although efficiency for conversion heating into turbulent energy in...

Here, a brain tumor classification method using the support vector machine (SVM) algorithm by utilizing discrete wavelet transform (DWT) transformation and feature extraction of gray-level co-occurrence matrix (GLCM) local binary pattern (LBP) has been implemented magnetic resonance imaging (MRI) image belong to low-grade glioma (LGG) or high-grade (HGG) group. SVM used as widely in research th...