- Tampa FL, US - Rochester MN, US Celine M. Vachon - Rochester MN, US Erin E. Fowler - Tampa FL, US
International Classification:
G06T 7/00 A61B 6/00 G06K 9/00 G06K 9/52 G06K 9/62
Abstract:
An automated percentage of breast density measure (PDa) that analyzes signal dependent noise (SDN) based on a wavelet expansion using full field digital mammography (FFDM). A matched case-control dataset is used with images acquired from a specific direct x-ray capture FFDM system. PDa is applied to the raw and clinical display representation images. Transforming (pixel mapping) of the raw image to another representation (raw-transformed) is performed using differential evolution optimization and investigated the influence of lowering the native spatial resolution of the image by a one-half. When controlling for body mass index, the quartile specific ORs for the associations of PDa with breast cancer varied with representation and resolution. PDa is a valid automated breast density measurement for a specific FFDM technology and compares well against PD (operator-assisted or the standard) when applied to either the raw-transformed or clinical display images from this FFDM technology.