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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Journal ArticleDOI
Microscopy image analysis of p63 immunohistochemically stained laryngeal cancer lesions for predicting patient 5-year survival
Konstantinos Ninos,Spiros Kostopoulos,Ioannis Kalatzis,Konstantinos Sidiropoulos,Konstantinos Sidiropoulos,Panagiota Ravazoula,George Sakellaropoulos,George S. Panayiotakis,George Economou,Dionisis Cavouras +9 more
TL;DR: An MIA-system is proposed that may be of assistance to physicians, as a second opinion tool in assessing the 5-year survival of patients with laryngeal cancer, and it has revealed useful information regarding differences in nuclei texture between 5- year survivors and non-survivors.
Book ChapterDOI
Modality Classification Using Texture Features
TL;DR: The aim of the paper is to investigate modality medical image classification problem by using a combination of several classification techniques and feature extraction algorithms over a set of medical images.
Journal ArticleDOI
Combination of Radiomics and Machine Learning with Diffusion-Weighted MR Imaging for Clinical Outcome Prognostication in Cervical Cancer
Ankush Jajodia,A. Gupta,Helmut Prosch,Marius E. Mayerhoefer,Swarupa Mitra,Sunil Pasricha,Anurag Mehta,Sunil K. Puri,Arvind Chaturvedi +8 more
TL;DR: The study is an effort to bridge the unmet need of translational predictive biomarkers in the stratification of uterine cervical cancer patients based on prognosis using supervised classification algorithms in the prediction of outcomes and prognosis.
Book ChapterDOI
Assessing estrogen receptors' status by texture analysis of breast tissue specimens and pattern recognition methods
Spiros Kostopoulos,Dionisis Cavouras,Antonis Daskalakis,Ioannis Kalatzis,Panagiotis Bougioukos,George C. Kagadis,Panagiota Ravazoula,George Nikiforidis +7 more
TL;DR: An image analysis system was developed for the quantitative assessment of estrogen receptor's (ER) positive status from breast tissue microscopy images, and high correlation was found between the histo-pathogist's and IAS scores, indicating IAS's reliability in the quantitative evaluation of ER as additional assistance to physician's assessment.
Journal ArticleDOI
Nuclear pattern recognition by two-parameter texture analysis.
TL;DR: High-resolution digitized images of nuclei are first standardized to render gray values invariant to staining and illumination conditions and these values may be considered as pure descriptors of the nuclear texture, as they represent the distribution of chromatin changes, disregarding any absolute densitometric and morphometric feature.
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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