Local binary pattern (LBP) is a nonparametric descriptor, which efficiently summarizes the
local structures of images. In recent years, it has aroused increasing interest in many areas …

OBJECTIVE: This paper focuses on the use of image-based machine learning techniques in
medical image analysis. In particular, we present some variants of local binary patterns …

Texture analysis is widely performed in the current time as it is considered as an intimate
property of the surface. It is widely used in the field of image processing, remote sensing …

We aim at improving quantitative measures of emphysema in computed tomography (CT)
images of the lungs. Current standard measures, such as the relative area of emphysema …

The aim of this work is to find the best way for describing a given texture using a local binary
pattern (LBP) based approach. First several different approaches are compared, then the …

Despite the progress made in the field of medical imaging, it remains a large area of open
research, especially due to the variety of imaging modalities and disease-specific …

We address a novel problem domain in the analysis of optical coherence tomography (OCT)
images: the diagnosis of multiple macular pathologies in retinal OCT images. The goal is to …

Medical image analysis has become a topic under the spotlight in recent years. There is a
significant progress in medical image research concerning the usage of machine learning …

This work is directed toward the development of a computer-aided diagnosis (CAD) system
to detect abnormalities or suspicious areas in digital mammograms and classify them as …

In 1979 Haralick famously introduced a method for analyzing the texture of an image: a set
of statistics extracted from the co-occurrence matrix. In this paper we investigate novel sets …