Journal ArticleDOI
Texture analysis using gray level run lengths
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.About:
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).read more
Citations
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Journal ArticleDOI
A computer-based image analysis method for assessing the severity of hip joint osteoarthritis
TL;DR: A computer-based image analysis method was developed for assessing the severity of hip osteoarthritis and the utilization of Laws’ textural measures improved the system classification performance, providing an overall classification accuracy of 94.4%.
Journal ArticleDOI
3D DCE-MRI Radiomic Analysis for Malignant Lesion Prediction in Breast Cancer Patients
TL;DR: In this article , a radiomic predictive model based on breast DCE-MRI, using only the strongest enhancement phase, with promising results in terms of accuracy and specificity in the differentiation of malignant from benign breast lesions.
Journal ArticleDOI
A Web-accessible Framework for Automated Storage with Compression and Textural Classification of Malaria Parasite Images
TL;DR: A web-accessible framework for automated storage of compressed microscopic images and texture-based screening of malaria parasite has been developed to provide rapid and efficient diagnosis even at remote public health clinics.
Journal ArticleDOI
Etiology-based classification of brain white matter hyperintensity on magnetic resonance imaging.
Mariana Leite,Leticia Rittner,Simone Appenzeller,Heloisa Helena Ruocco,Roberto de Alencar Lotufo +4 more
TL;DR: In this article, a computerized method to distinguish tissue containing white matter lesions of different etiologies (e.g., demyelinating or ischemic) using texture-based classifiers was proposed.
Proceedings ArticleDOI
Computer assisted characterization of liver tissue using image texture analysis techniques on B-scan images
TL;DR: In this article, the classification of B-scan ultrasonic liver images using image texture analysis techniques is investigated, including Gray Level Difference Statistics (GLDS), the Gray Level Run Length Statistics (RUNL), the Spatial Gray Level Dependence Matrices (SGLDM), and Fractal Dimension Texture Analysis (FDTA).
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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