The present study proposed a computer-aided diagnosis system based on radiomic features extracted through magnetic resonance imaging to determine the isocitrate dehydrogenase status in glioblastomas. Magnetic resonance imaging data were obtained from 32 patients with wild-typeisocitrate dehydrogenase and 7 patients with mutant isocitrate dehydrogenase in glioblastomas. Radiomic features, namely...

This paper presents two feature extraction methods and two decision methods to retrieve images having some section in them that is like the user input image. The features used are variances of gray level co-occurrences and lineangle-ratio statistics constituted by a 2-D histogram of angles between two intersecting lines and ratio of mean gray levels inside and outside the regions spanned by tho...

In this paper we present an approach to music genre classification which converts an audio signal into spectrograms and extracts texture features from these time-frequency images which are then used for modeling music genres in a classification system. The texture features are based on Local Binary Pattern, a structural texture operator that has been successful in recent image classification re...

UNLABELLED Intratumoral uptake heterogeneity in (18)F-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural feature analysis is a promising method for its quantification. An open issue associated with textural features for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volu...

Real-world images usually contain vivid contents and rich textural details, which will complicate the manipulation on them. In this paper, we present a content-aware synthesis method to enhance content-aware image retargeting. By detecting the textural regions in an image, the image content can be synthesized rather than simply distorted or cropped. This method enables the manipulation of textu...

Image textural analysis technology has been widely used in the design of automated defect detection systems. Because the presence of defects may change the textural features of an image, a reference image without defects can be compared with the test image to detect whether there are any defects. However, besides defects, the deflection of the input test image could also change its textural fea...

A novel approach using volumetric texture and reduced-spectral features is presented for hyperspectral image classification. Using this approach, the volumetric textural features were extracted by volumetric gray-level co-occurrence matrices (VGLCM). The spectral features were extracted by minimum estimated abundance covariance (MEAC) and linear prediction (LP)-based band selection, and a semi-...

A computer software system is designed for the automatic discrimination of benign tumor from malignant tumor in brain CT examinations. Image analysis methods were applied to the images of 40 benign images and 40 malignant images. Textural features extracted from the gray level co-occurrence matrix of the tumor images and back propagation neural network classifier were employed for the design of...