Evaluation of non-Gaussian statistical properties of digital breast tomosynthesis images: an initial study

Kai Yang; Craig K. Abbey; Bruno Barufaldi; Xinhua Li; Theodore A. Marschall; Bob Liu

doi:10.1117/12.3026747

29 May 2024 Evaluation of non-Gaussian statistical properties of digital breast tomosynthesis images: an initial study

Kai Yang, Craig K. Abbey, Bruno Barufaldi, Xinhua Li, Theodore A. Marschall, Bob Liu

Proceedings Volume 13174, 17th International Workshop on Breast Imaging (IWBI 2024); 1317408 (2024) https://doi.org/10.1117/12.3026747
Event: 17th International Workshop on Breast Imaging (IWBI 2024), 2024, Chicago, IL, United States

Abstract

To quantitatively study the non-Gaussian statistical properties of breast parenchymal texture on digital breast tomosynthesis (DBT) images acquired from two vendors. This IRB approved retrospective study included patients who had normal screening DBT exams performed on a GE unit in January 2018 and normal screening DBT exams in adjacent years (2017 or 2019) from a Hologic unit. We use Laplacian Fractional Entropy (LFE) as a measure of the non-Gaussian statistical properties from DBT images. Fifty-four Gabor filters that spanned 9 center frequencies from 0.15 to 2.0 cyc/mm were constructed at six different orientations (0 to150 deg). Filter responses were generated by convolving each filter with a Cranial-Caudal (CC) view DBT slice. All responses from 6 mm inside the boundary of the breast in each slice were used to form response histograms from which the LFE measures at different frequencies were estimated. The histograms binned the central 99% of the responses. The averaged LFE results among the central 80% of DBT slices were reported for each exam and compared between the two vendors. A total of 7,894 DBT slices from 69 exams in 25 women were included. Significant differences in LFE, were observed between DBT images acquired from Hologic and GE, using images from the same 25 patients in consecutive years. There are quantitative differences in non-Gaussian properties from the presentation of breast imaging texture between DBT vendors. Our findings have relevance and importance for external validation of AI algorithms across vendors.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Kai Yang, Craig K. Abbey, Bruno Barufaldi, Xinhua Li, Theodore A. Marschall, and Bob Liu "Evaluation of non-Gaussian statistical properties of digital breast tomosynthesis images: an initial study", Proc. SPIE 13174, 17th International Workshop on Breast Imaging (IWBI 2024), 1317408 (29 May 2024); https://doi.org/10.1117/12.3026747

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Digital breast tomosynthesis

Breast

Histograms

Frequency response

Image processing

Spatial frequencies

Visualization

Keywords/Phrases

Search In:

Publication Years