Is it blur or is it texture? An analysis of computational blur and texture measures commonly used in medical image analysis.

ABSTRACT:

Purpose

In this work, we endeavor to investigate how texture information may contribute to the response of a blur measure (BM) with motivation rooted in mammography. This is vital as the interpretation of the BM is typically not evaluated with respect to texture present in an image. We are particularly concerned with lower scales of blur (≤1  mm) as this blur is least likely to be detected but can still have a detrimental effect on detectability of microcalcifications.

Approach

Three sets of linear models, where BM response was modeled as a linear combination of texture information determined by texture measures (TMs), were constructed from three different datasets of equal-blur-level images; one of computer-generated mammogram-like clustered lumpy background (CLB) images an

SUBMITTER: Chen AW 

PROVIDER: S-EPMC10207694 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature