Sentence examples for classification of tissues from inspiring English sources

Multi-energy computed tomography (CT) refers to the use of spectral data allowing differentiation and classification of tissues to obtain material-specific images [1].

This information can be provided by X-rays for the classification of tissues and can be obtained visually when tissue samples are placed in a test system, such as in a Petri dish in vitro.

This innovative approach combines the HMRF-EM parametric approach with the nonparametric Parzen window classifier facilitating robust classification of tissues with a well-defined Gaussian distribution (WM and GM) and those exhibiting skewed distributions (CSF and WMSA).

Cell counts were performed by two different investigators who were blind to the classification of tissues.

Motivation: Classification of tissues using static gene-expression data has received considerable attention.

Discriminant analysis for classification of tissues types [ 9] was performed to determine the discriminative ability of the screened miRNAs.

Thorough characterization and classification of tissue culture induced chromosome aberrations have led to a better understanding of somaclonal variation (Lee and Phillips 1988; Bairu et al. 2011).

Accordingly, the aim of this study was to develop a tissue characterization mapping (TCM) technique by combining the established LGE method with our novel percent edema mapping (PEM) method to enable the classification of tissue in the different MRI voxels as healthy, edematous, necrotic, hemorrhagic, or scarred using a canine model of reperfused MI.

Our aim was to develop a tissue characterization mapping (TCM) technique by combining late gadolinium enhancement (LGE) with our novel percent edema mapping (PEM) approach to enable the classification of tissue represented by MRI voxels as healthy, myocardial edema (ME), necrosis, myocardial hemorrhage (MH), or scar.

Classification of tissue specimens (i.e. presence or absence of tumour) was performed without other pathological or clinical data.

Microarray cancer datasets, organized as samples versus genes fashion, are being used for classification of tissue samples into benign and malignant or their subtypes.