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Computational tools for quantitative breast morphometry based on 3D scans.

Abstract：

:Quantitative analysis of breast morphometry is critical to breast plastic surgery. Recently, three-dimensional (3D) photography has emerged as a strong new alternative for breast morphometry analysis in comparison to other existing techniques. 3D photography enables the capture of the entire breast surface topology virtually in a single snapshot and without any direct contact with the patient, thus causing minimal discomfort. In this paper, we present a set of computational tools for the quantitative analysis of two key morphological properties of the breast that are of interest to breast plastic surgery based on 3D scans, namely breast shape and volume. The breast shape is modeled using a compact geometric model capable of capturing the global shape of the breast with very few parameters. Specifically, the shape model is deduced by applying a set of five global deformations to a geometric primitive. These deformations, defined using very intuitive parameters, closely model the key shape variables that surgeons inherently use to describe the overall shape of the breast. Patient-specific parameters of the breast shape model are automatically recovered by fitting a generic breast shape model to the 3D scan of the patient's breast using a physics-based deformable model framework. The mean error of fit between the automatically fitted shape model and the actual breast surface for 12 subjects varied between 0.9 and 2.6 mm. These results are very encouraging considering the fact that only 17 parameters are used to determine the shape of the breast. The breast volume is estimated automatically by first localizing the breast on a 3D scan of the patient's torso and then computing the volume enclosed between an interpolated breast-less torso surface and the actual breast. The volume estimated by the proposed method was found to be within the intra-operator variability among five segmentation trials performed manually by an expert on 3D torso scans of three subjects.

journal_name

Ann Biomed Eng

journal_title

Annals of biomedical engineering

authors

Chen D,Chittajallu DR,Passalis G,Kakadiaris IA

doi

10.1007/s10439-010-9971-z

subject

Has Abstract

pub_date

2010-05-01 00:00:00

pages

1703-18

issue

eissn

0090-6964

issn

1573-9686

journal_volume

pub_type

杂志文章

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Computational tools for quantitative breast morphometry based on 3D scans.