Abstract

Percentage mammographic breast density, a measure of the fraction of radio-fibroglandular tissue in breast, is an indicator for high risk of developing breast cancer. Although the breast cancer development risk with increasing breast density is well established, this information is generally not used clinically due to the lack of quantitative, unsupervised methods to evaluate the breast density. Visual estimates produce only qualitative results and are irreproducible. Hence, semi-automatic thresholding methods, in which the segmentation is performed by an expert but the percentage are is calculated by computer, are preferred. Here, we present the results of a fully automated method to analyze digital mammograms for breast density assessment. The comparison, using Pearson's product-moment correlation, for the intra-observer variability resulted in and for the first data set for two radiologists, respectively. Similarly, the inter-observer comparison for the two radiologists yielded and for the first and second data sets. The automatic evaluation algorithm results in comparison to radiologists assessment gave and for the first data set and and for the second set. The significance level for all the coefficients was P < 0.0001. The correlations between the radiologists and automatic estimates imply that the explained variances in each case are comparable with the agreement between the two radiologists. A comparison of this method with the experts' evaluation, obtained using the current standard of semi-automatic thresholding technique, indicates that the new unsupervised method for breast density estimation is quite accurate, reproducible and ready for clinical use.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.