Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach.

Published

Journal Article

The discrimination between benign and malignant adnexal masses in ultrasound images represents one of the most challenging problems in gynecologic practice. In the study described here, a new method for automatic discrimination of adnexal masses based on a neural networks approach was tested. The proposed method first calculates seven different types of characteristics (local binary pattern, fractal dimension, entropy, invariant moments, gray level co-occurrence matrix, law texture energy and Gabor wavelet) from ultrasound images of the ovary, from which several features are extracted and collected together with the clinical patient age. The proposed technique was validated using 106 benign and 39 malignant images obtained from 145 patients, corresponding to its probability of appearance in general population. On evaluation of the classifier, an accuracy of 98.78%, sensitivity of 98.50%, specificity of 98.90% and area under the curve of 0.997 were calculated.

Full Text

Duke Authors

Cited Authors

  • Aramendía-Vidaurreta, V; Cabeza, R; Villanueva, A; Navallas, J; Alcázar, JL

Published Date

  • March 2016

Published In

Volume / Issue

  • 42 / 3

Start / End Page

  • 742 - 752

PubMed ID

  • 26715189

Pubmed Central ID

  • 26715189

Electronic International Standard Serial Number (EISSN)

  • 1879-291X

International Standard Serial Number (ISSN)

  • 0301-5629

Digital Object Identifier (DOI)

  • 10.1016/j.ultrasmedbio.2015.11.014

Language

  • eng