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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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Journal ArticleDOI

Automated quantification of ultrasonic fatty liver texture based on curvelet transform and SVD

TL;DR: A novel algorithm to discriminate the texture of fatty liver based on curvelet transform and SVD is proposed, which gave an accuracy of 96.9% in classifying the four grades of fat in the liver.
Journal ArticleDOI

Differentiation of Pelvic Osteosarcoma and Ewing Sarcoma Using Radiomic Analysis Based on T2-Weighted Images and Contrast-Enhanced T1-Weighted Images.

TL;DR: To differentiate OS from EWS of the pelvis using the authors' multiparametric MRI-based radiomic analysis could preoperatively improve diagnostic accuracy and greatly contribute to therapy planning.
Journal ArticleDOI

Exploration of temporal stability and prognostic power of radiomic features based on electronic portal imaging device images

TL;DR: This study suggests a novel approach to select temporally stable radiomic features, which could hold prognostic powers in lung cancer patients, which were found to be temporallystable for various quantization levels.
Book ChapterDOI

Multi-Image Texture Analysis in Classification of Prostatic Tissues from MRI. Preliminary Results

TL;DR: Experiments with several sets of textural features and four classification methods showed that the application of multi-image texture analysis could improve the classification accuracy in comparison to single- image texture analysis.
Journal ArticleDOI

Can Laws Be a Potential PET Image Texture Analysis Approach for Evaluation of Tumor Heterogeneity and Histopathological Characteristics in NSCLC

TL;DR: In this article, the association between the textural features obtained from 18F-FDG images, metabolic parameters (SUVmax, SUVmean, MTV, TLG), and tumor histopathological characteristics (stage and Ki-67 proliferation index) in non-small cell lung cancer (NSCLC) was investigated.
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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