This paper presents new structural statistical matrices which are gray level size zone matrix
(SZM) texture descriptor variants. The SZM is based on the cooccurrences of size/intensity of …

This paper describes the sequence of construction of a cell nuclei classification model by the
analysis, the characterization and the classification of shape and texture. We describe first …

Texture analysis is a major task in many areas of computer vision and pattern recognition,
including biological imaging. Indeed, visual textures can be exploited to distinguish specific …

Texture analysis refers to the branch of imaging science that is concerned with the
description of characteristic image properties by textural features. However, there is no …

Texture analysis describes a variety of image analysis techniques that quantify the variation
in intensity and pattern. This paper provides an overview of several texture analysis …

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 …

Background The aim of the study was to assess whether texture analysis is feasible for
automated identification of epithelium and stroma in digitized tumor tissue microarrays …

Two approaches to the characterization of three-dimensional (3-D) textures are presented:
one based on gradient vectors and one on generalized co-occurrence matrices. They are …

Millions of white blood cells are manually classified in laboratories using microscopes, a
painstaking and subjective task. A trained medical technician takes about 15min to evaluate …

Automatic recognition of different tissue types in histological images is an essential part in
the digital pathology toolbox. Texture analysis is commonly used to address this problem; …