Automated spatial alignment of 3D torso images

Abstract

This paper describes an algorithm for automated spatial alignment of three-dimensional (3D) surface images in order to achieve a pre-defined orientation. Surface images of the torso are acquired from breast cancer patients undergoing reconstructive surgery to facilitate objective evaluation of breast morphology pre-operatively (for treatment planning) and/or post-operatively (for outcome assessment). Based on the viewing angle of the multiple cameras used for stereophotography, the orientation of the acquired torso in the images may vary from the normal upright position. Consequently, when translating this data into a standard 3D framework for visualization and analysis, the co-ordinate geometry differs from the upright position making robust and standardized comparison of images impractical. Moreover, manual manipulation and navigation of images to the desired upright position is subject to user bias. Automating the process of alignment and orientation removes operator bias and permits robust and repeatable adjustment of surface images to a pre-defined or desired spatial geometry.

3D surface imaging of the human female torso in upright to supine positions

“…Our team has developed software for visualization, manipulation, and analysis of 3D surface data. 9 , 16 , 20 , 21 The analysis modules allow for manual annotation (via mouse click) of fiducial points on 3D images and computation of both distance (line-of-sight and contoured) and volume measurements. The visualization framework permits free full 360° rotation of the torso, thereby enabling the annotation of fiducial points with ease.…”

“… 1 – 3 , 5 – 21 Typically, image acquisition occurs with the patient in an upright, standing pose. 1 – 9 , 11 , 14 – 21 A standing pose is optimal for imaging with the routine configuration of 3D camera systems and because this is the standard position for subjective evaluation of breast aesthetics.…”

3D computer technology addresses body-image issues of breast reconstruction

“…9,10 With such measurements, we can investigate surgical options that include different types of mastectomies 6 and reconstruction procedures. 9,10 Our goal is to streamline our analyses through techniques such as development of algorithms that automatically align images to a defined orientation 4 and locate fiducial points. 5,7,11 For example, we have developed accurate methods for fiducial point localization using 3D surface-curvature analysis coupled with 2D texture analysis (see Figure 1).…”

“…This article describes our approach to quantifying a patient's appearance via imaging and 3D modeling techniques. [1][2][3][4][5][6][7][8][9][10][11] We note, however, that developing a greater understanding of patient preferences in terms of quality-of-life measures such as body image 12 and modeling the decision-making process for breast reconstruction 13 are equally important aspects of our research program.…”

Computation of Breast Ptosis from 3D Scans of Torso

“…Surface curvature analysis can be used to highlight the shape of the underlying 3D surface, thus it plays an important role in ptosis classification. To calculate Gaussian curvature, we used a toolbox developed by Gabriel Peyre [19] based on the algorithms proposed by Cohen-Steiner et al [20,21]. We employed a pseudo-color visualization method for viewing the Gaussian curvature of the 3D mesh.…”