Image retrieval system is one of a challenging topic and is not yet finalized. A number of features extraction methods has been proposed, for example Gray Level CoOccurrence Matrix (GLCM), Texton Co-Occurrence Histogram (TCM), Multi Texton Histogram (MTH), Micro Stucture Descriptor (MSD), Enhanced Micro Structure Descriptor (EMSD) and Color difference Histogram (CDH). However, the precision rat...

It has been shown that the intratumor heterogeneity can be characterized with quantitative analysis of the [18]F-FDG PET image data. The existing models employ multiple parameters for feature extraction which makes it difficult to implement in clinical settings for the quantitative characterization. This article reports an easy-to-use and differential SUV based model for quantitative assessment...

UNLABELLED BACKGROUND Several algorithms from the literature were compared with the original random walk (RW) algorithm for brain perfusion heterogeneity quantification purposes. Algorithms are compared on a set of 210 brain single photon emission computed tomography (SPECT) simulations and 40 patient exams. METHODS Five algorithms were tested on numerical phantoms. The numerical anthropom...

Background and study aims  Bubbles can impair visualization of the small bowel (SB) mucosa during capsule endoscopy (CE). We aimed to develop and validate a computed algorithm that would allow evaluation of the abundance of bubbles in SB-CE still frames. Patients and methods  Two sets of 200 SB-CE normal still frames were created. Two experienced SB-CE readers analyzed both sets of images twi...

Texture is an important spatial feature, useful for identifying objects or regions of interest in an image. Statistical and structural approaches have extensively studied in the texture analysis and classif ication whereas little work has reported to integrate them. One of the most popular statistical methods used to measure the textural information of images is the grey-level co-occurrence mat...

The long-time historical evolution and recent rapid development of Beijing, China, present before us a unique urban structure. A 10-metre spatial resolution SPOT panchromatic image of Beijing has been studied to capture the spatial patterns of the city. Supervised image classifications were performed using statistical and structural texture features produced from the image. Textural features, i...

This study proposed an approach to retrieve images based on texture features using GLCM and image subblocks. Each image is divided into three rows and three columns with equal sizes. Texture features are extracted based on GLCM (Gray Level Co-occurrence Matrix) using four statistical features that is contrast, homogeneity, energy and correlation. The features are calculated in four directions (...

Texture information plays an important role in image analysis. Although several descriptors have been proposed to extract and analyze texture, the development of automatic systems for image interpretation and object recognition is a difficult task due to the complex aspects of texture. Scale is an important information in texture analysis, since a same texture can be perceived as different text...

Glioblastoma multiforme (GBM) is the most common malignant primary tumor of the central nervous system, characterized among other traits by rapid metastatis. Three tissue phenotypes closely associated with GBMs, namely, necrosis (N), contrast enhancement (CE), and edema/invasion (E), exhibit characteristic patterns of texture heterogeneity in magnetic resonance images (MRI). In this study, we p...