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.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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Multiple-Instance Learning for Anomaly Detection in Digital Mammography
TL;DR: A computer-aided detection and diagnosis system for breast cancer, the most common form of cancer among women, using mammography, which relies on the Multiple-Instance Learning (MIL) paradigm and suggests that anomaly detectors can be advantageously trained on large medical image archives, without the need for manual segmentation.
Journal ArticleDOI
Application of Hyperspectral Imaging to Discriminate the Variety of Maize Seeds
TL;DR: In this paper, the least square support vector machine (SVM) was used to classify different varieties of maize seeds based on spectral, textural, or fusion data, and the resulting classification maps were developed to visualize different maize seeds.
Journal ArticleDOI
Increasing the discrimination power of the co-occurrence matrix-based features
TL;DR: This paper is concerned with an approach to exploiting information available from the co-occurrence matrices computed for different distance parameter values by fitting a polynomial of degree n to each of 14 Haralick's coefficients computed from the average co- Occurrence Matrices evaluated for several distance parametervalues.
Journal ArticleDOI
Quantitative identification of nonmuscle-invasive and muscle-invasive bladder carcinomas: a multiparametric MRI radiomics analysis
Xiaopan Xu,Xi Zhang,Qiang Tian,Huanjun Wang,Long-Biao Cui,Shurong Li,Xing Tang,Baojuan Li,Jose Dolz,Ismail Ben Ayed,Zhengrong Liang,Jing Yuan,Peng Du,Hongbing Lu,Yang Liu +14 more
TL;DR: This data indicates that preoperative discrimination between nonmuscle‐invasive bladder carcinomas and muscle-invasive ones (MIBC) is very crucial in the management of patients with bladder cancer (BC).
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Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Predict Gleason Score Upgrading in Intermediate-Risk 3 + 4 = 7 Prostate Cancer.
Radu Rozenberg,Rebecca E. Thornhill,Trevor A. Flood,Shaheed W. Hakim,Christopher S. Lim,Nicola Schieda +5 more
TL;DR: In this study, whole-lesion mean ADC, ADC ratio, and ADC histogram analysis were not predictive of pathologic upgrading of Gleason score (GS) upgrading in 3 + 4 = 7 prostate cancer after RP and regression models combining texture features improved the prediction of GS upgrading.
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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