Maximum-likelihood estimation of thickness with a linear-scatter model for mammography
Document Type
Conference Proceeding
Publication Date
1-1-2022
Abstract
The objective of this work was to create a MLEM software-based scatter correction algorithm for removing the effect of Compton Scatter from mammography images acquired without scatter grid or with analyzer-less interferometry. We developed an MLEM algorithm with an efficient linear scatter model to estimate the thickness of compressed breast and evaluated the algorithm with breast images acquired with the GEANT4 Monte Carlo software. The thicknesses estimated from the algorithm on the GEANT4 images were compared to the true geometric thicknesses of the ellipsoid for each pixel of the detector and matched to within 2mm RMS error.
Publication Source (Journal or Book title)
Progress in Biomedical Optics and Imaging Proceedings of SPIE
Recommended Citation
Smith, B., & Dey, J. (2022). Maximum-likelihood estimation of thickness with a linear-scatter model for mammography. Progress in Biomedical Optics and Imaging Proceedings of SPIE, 12031 https://doi.org/10.1117/12.2611970