Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer.

ABSTRACT:

Background and objective

This study aims to develop and evaluate a unique global mammographic image feature analysis scheme to predict likelihood of a case depicting the detected suspicious breast mass being malignant for breast cancer.

Methods

From the entire breast area depicting on the mammograms, 59 features were initially computed to characterize the breast tissue properties at both spatial and frequency domain. Given that each case consists of two cranio-caudal and two medio-lateral oblique view images of left and right breasts, two feature pools were built, which contain the computed features from either two positive images of one breast or all the four images of two breasts. Next, for each feature pool, a particle swarm optimization (PSO) method was applied to determ

SUBMITTER: Chen X 

PROVIDER: S-EPMC7081451 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature