Three-Dimensional Mass Reconstruction in Mammography
Abstract
In this paper, we present a novel method for reconstructing the 3-D shapes of masses. We first use the Shape from Silhouettes technique to get an approximation to the 3-D shape of the mass. We calculate the centroid of the mass in the 2-D images and back-project them to get their intersection in 3-D. We then apply a novel iterative method, which is derived from ART (Algebraic Reconstruction Technique), to refine the 3-D shape of the mass. The thickness of the masses is calculated according to the h _int representation. We use the thickness of the masses in the CC and MLO or LM views to refine the 3-D approximation to the reconstructed shape of the mass. We find that the mean deviation rate of the reconstruction of a pair of benign masses is much larger than that of malignant masses, which can be used as a criterion of classifying a mass into malignant or benign.
Cite
Text
Shao and Brady. "Three-Dimensional Mass Reconstruction in Mammography." European Conference on Computer Vision, 2004. doi:10.1007/978-3-540-27816-0_21Markdown
[Shao and Brady. "Three-Dimensional Mass Reconstruction in Mammography." European Conference on Computer Vision, 2004.](https://mlanthology.org/eccv/2004/shao2004eccv-three/) doi:10.1007/978-3-540-27816-0_21BibTeX
@inproceedings{shao2004eccv-three,
title = {{Three-Dimensional Mass Reconstruction in Mammography}},
author = {Shao, Ling and Brady, Michael},
booktitle = {European Conference on Computer Vision},
year = {2004},
pages = {246-256},
doi = {10.1007/978-3-540-27816-0_21},
url = {https://mlanthology.org/eccv/2004/shao2004eccv-three/}
}