Proceedings ArticleDOI
Rapid Texture Identification
Kenneth I. Laws
- Vol. 0238, pp 376-381
TLDR
In this article, the texture energy approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation.Abstract:
A method is presented for classifying each pixel of a textured image, and thus for segmenting the scene. The "texture energy" approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation. Normalization by the local mean and standard deviation eliminates the need for histogram equalization. Rotation-invariance can also be achieved by using averages of the texture energy features. The convolution masks are separable, and can be implemented with 1-dimensional (vertical and horizontal) or multipass 3x3 convolutions. Special techniques permit rapid processing on general-purpose digital computers.read more
Citations
More filters
Proceedings ArticleDOI
Automated quantification of epicardial adipose tissue in cardiac magnetic resonance imaging
Alexandra Cristobal-Huerta,Angel Torrado-Carvajal,Norberto Malpica,María Luaces,Juan Antonio Hernández-Tamames +4 more
TL;DR: A novel approach for the automated quantification of EAT using “a priori” anatomical information is presented and results for 10 morbidly obese patients show no significant differences between manual and automatic quantification with a remarkable time and effort saving between them.
Journal ArticleDOI
Detection of pathologic liver using ultrasound images
TL;DR: The hepatorenal coefficient proved to be a good parameter for steatosis detection with calculated sensitivity and specificity values of 0.90 and 0.88, respectively, and it was observed the hepatorenAl coefficient is not influenced by the ultrasound machine parameters.
Journal ArticleDOI
Architectural Distortion Detection in Mammogram using Contourlet Transform and Texture Features
S. Anand,R. Aynesh Vijaya Rathna +1 more
TL;DR: The proposed methods have significant result in detecting the architectural distortion in mammograms of interval cancer cases and the reduction of the region of interests.
Journal ArticleDOI
Specificity improvement of a CAD system for multiparametric MR prostate cancer using texture features and artificial neural networks
TL;DR: A classifier composed by 3 Artificial Neural Networks (ANN) able to distinguish between malignant and healthy areas through a voting strategy is developed able to improve the performance of a CAD system in term of reduction of FPs findings, without affecting the sensitivity.
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.
References
More filters
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.
ReportDOI
Textured Image Segmentation
TL;DR: In this article, texture energy is measured by filtering with small masks, typically 5x5, then with a moving-window average of the absolute image values, leading to a simple class of texture energy transforms, which perform better than any of the preceding methods.