Journal ArticleDOI
Application of artificial neural networks for the classification of liver lesions by image texture parameters
TLDR
In this article, a multilayered back-propagation neural network was used for liver lesion classification using B-scan ultrasound images for normal, hemangioma and malignant livers.Abstract:
Ultrasound imaging is a powerful tool for characterizing the state of soft tissues; however, in some cases, where only subtle differences in images are seen as in certain liver lesions such as hemangioma and malignancy, existing B-scan methods are inadequate. More detailed analyses of image texture parameters along with artificial neural networks can be utilized to enhance differentiation. From B-scan ultrasound images, 11 texture parameters comprising of first, second and run length statistics have been obtained for normal, hemangioma and malignant livers. Tissue characterization was then performed using a multilayered backpropagation neural network. The results for 113 cases have been compared with a classification based on discriminant analysis. For linear discriminant analysis, classification accuracy is 79.6% and with neural networks the accuracy is 100%. The present results show that neural networks classify better than discriminant analysis, demonstrating a much potential for clinical application.read more
Citations
More filters
Journal ArticleDOI
Influence of the measurement method of features in ultrasound images of the thyroid in the diagnosis of Hashimoto's disease.
Robert Koprowski,Anna Korzynska,Zygmunt Wróbel,Witold Zieleźnik,Agnieszka Witkowska,Justyna Małyszek,Waldemar Wójcik +6 more
TL;DR: The conducted sensitivity assessment confirms that changes in the position and size of the ROI have little effect on sensitivity and specificity, and the value of ACC for the method using decision trees as a classifier is equal to 84% for the analyzed data.
Journal ArticleDOI
Examination of cyclic changes in bovine luteal echotexture using computer-assisted statistical pattern recognition techniques.
TL;DR: The results of this study show that statistical pattern recognition techniques provide new information about the luteal glands, thus facilitating a more accurate differentiation between different cycle stages in cows.
Book ChapterDOI
Systematic Construction of Texture Features for Hashimoto's Lymphocytic Thyroiditis Recognition from Sonographic Images
TL;DR: It is shown that a network of weak Bayes classifiers using 4-cliques as features and combined by majority vote achieves diagnosis recognition accuracy of 92%, as evaluated on a set of 741 B-mode sonographic images from 39 subjects.
Journal ArticleDOI
Detection and Classification of Focal Liver Lesions using Support Vector Machine Classifiers
TL;DR: Two computer aided diagnostic systems designed to detect and classify focal liver lesions such as Cyst, Hemangioma, Hepatocellular carcinoma and Metastases outperforms the neural network based diagnostic system designed for the same purpose by providing 96.6% classification accuracy for typical cases and 85.3% for atypical cases.
Journal ArticleDOI
Application of neural networks for the analysis of intravascular ultrasound and histological aortic wall appearance-an in vitro tissue characterization study.
Lukasz Chrzanowski,Jarosław Drożdż,Michal Strzelecki,Maria Krzemińska-Pakuła,Kazimierz Jędrzejewski,Jarosław D. Kasprzak +5 more
TL;DR: The study shows that ANNs are a potentially effective tool for assessment of IVUS aortic images and that the ANN-based approach was the most effective in discriminant analysis.
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.
Journal ArticleDOI
An introduction to computing with neural nets
TL;DR: This paper provides an introduction to the field of artificial neural nets by reviewing six important neural net models that can be used for pattern classification and exploring how some existing classification and clustering algorithms can be performed using simple neuron-like components.
Book
Pathologic basis of disease
TL;DR: The objective is to establish an experimental procedure and show direct AFM progression from EMT to EMT using a simple, straightforward, and reproducible procedure.
Journal ArticleDOI
A Comparative Study of Texture Measures for Terrain Classification
TL;DR: In this paper, three standard approaches to automatic texture classification make use of features based on the Fourier power spectrum, on second-order gray level statistics, and on first-order statistics of gray level differences, respectively.
Journal ArticleDOI
Use of gray value distribution of run lengths for texture analysis
TL;DR: The gray value distribution of the runs is proposed to be used to define two new features, viz., low gray level run emphasis ( LGRE) and high gray levelrun emphasis ( HGRE).