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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.
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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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Detection of underlying characteristics of nuclear chromatin patterns of thyroid tumor cells using texture and factor analyses

TL;DR: This technique, using texture and factor analyses, is useful in the detection of underlying characteristics of nuclear chromatin patterns in aspiration biopsy cytology, and nuclei of papillary carcinoma showed higher contrast of Chromatin patterns than did those of the benign group.
Journal ArticleDOI

Integrating radiologist feedback with computer aided diagnostic systems for breast cancer risk prediction in ultrasonic images: An experimental investigation in machine learning paradigm

TL;DR: Improving the clinical efficiency of ultrasound based CAD systems for classification of breast lesions by integrating back-propagation artificial neural network (BPANN), support vector machine (SVM) and radiologist feedback and integrating expert opinion in CAD systems improves its overall performance.
Journal ArticleDOI

Practical guidelines for handling head and neck computed tomography artifacts for quantitative image analysis.

TL;DR: It is concluded that simply removing slices affected by streak artifacts can enable these scans to be included in radiomics studies and that contours of structures can abut bone without being affected by beam hardening if needed.
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Hybrid approach to classification of focal and diffused liver disorders using ultrasound images with wavelets and texture features

TL;DR: The proposed technique, which is an application of texture feature extraction on transform domain images, gives an overall classification accuracy of 91% for a combination of ten classes of similar looking diseases which is appreciable than the spatial domain only techniques for liver disease classification from ultrasound images.
Journal ArticleDOI

Risk stratification of 2D ultrasound-based breast lesions using hybrid feature selection in machine learning paradigm

TL;DR: A new hybrid feature selection scheme is used to determine most relevant features for classification of benign and malignant tumors in breast ultrasound images to achieve significantly higher classification accuracy.
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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