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Journal ArticleDOI

Texture analysis using gray level run lengths

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TLDR
In this paper, a set of texture features based on gray level run lengths is described, and good classification results are obtained with these features on a sets of samples representing nine terrain types.
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This article is published in Computer Graphics and Image Processing.The article was published on 1975-06-01. It has received 1848 citations till now. The article focuses on the topics: Image texture & Texture (geology).

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Citations
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Proceedings ArticleDOI

Automatic Classification of Focal Lesions in Ultrasound Liver Images using Principal Component Analysis and Neural Networks

TL;DR: This paper summarizes the various statistical and spectral texture parameter extraction processes, optimal feature selection techniques and automated classification procedures involved in the possibilities of automatic classification of the ultrasound liver images into four classes-normal, cyst, benign and malignant masses.
Journal ArticleDOI

Automatic Classification of Specific Melanocytic Lesions Using Artificial Intelligence

TL;DR: A proposed system can not only help to precisely diagnose the type of the skin mole but also decrease the amount of biopsies and reduce the morbidity related to skin lesion excision.
Journal ArticleDOI

Pre-treatment CT radiomics to predict 3-year overall survival following chemoradiotherapy of esophageal cancer.

TL;DR: A RF model predicting 3-year overall survival based on pretreatment CT radiomic features was developed and validated in two independent datasets of esophageal cancer patients and had better prognostic power compared to the model using standard clinical variables.
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Zizyphus spina-christi protects against carbon tetrachloride-induced liver fibrosis in rats.

TL;DR: Administration of ZSC may be useful in the treatment and prevention of hepatic fibrosis and reduces the expression of alpha-smooth muscle actin, the deposition of types I and III collagen in CCl(4)-injured rats.
References
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Journal ArticleDOI

Textural Features for Image Classification

TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Journal ArticleDOI

Gray-Level Manipulation Experiments for Texture Analysis

TL;DR: Some gray-level manipulation techniques are described, the first of which involves changing thegray-level distribution within the picture, and a method for extracting relatively noise-free objects from a noisy background is described.
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