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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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Computer aided diagnostic system for ultrasound liver images: A systematic review

TL;DR: An in-depth overview of the Computer aided diagnostic (CAD) system’s usage for liver cancer is presented and specific methods that are commonly used in most of the algorithms proposed for computerized tissue characterization are reviewed.
Proceedings ArticleDOI

Multi-channels statistical and morphological features based mitosis detection in breast cancer histopathology

TL;DR: The proposed framework includes comprehensive analysis of first and second order statistical features together with morphological features in selected color channels and a study on balancing the skewed dataset using SMOTE method for increasing the predictive accuracy of mitosis classification.
Journal ArticleDOI

A New Markov Random Field Segmentation Method for Breast Lesion Segmentation in MR images.

TL;DR: Improved-Markov Random Field (I-MRF) method for breast lesion segmentation in MR images is presented, which doesn’t use the Iterative Conditional Mode (ICM) method or Simulated Annealing (SA) for class membership estimation of each pixel.
Journal ArticleDOI

Elaboration of a multimodal MRI-based radiomics signature for the preoperative prediction of the histological subtype in patients with non-small-cell lung cancer

TL;DR: Non-invasive histological subtype stratification of NSCLC can be done favorably using multimodal MRI radiomics features and the Radscore with the semantic clinical features, a radiomics–clinical nomogram was developed, and its overall performance was evaluated.
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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