Computational Modeling of Breast Shape Using Spherical Harmonics
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As the number of cosmetic and reconstructive breast surgeries performed have been steadily increasing over the years, there is a greater need for improved technologies, such as developing a computational three-dimensional breast model. The breast model will be an invaluable tool for surgeons in surgical planning and during clinical consultations with patients in shared decision making. In this dissertation, a breast model using spherical harmonics is presented. A 3D breast surface image is converted to a spherical harmonic (SPHARM) description, which is represented with three sets of coefficients and can be used to reconstruct a computational model of the breast. Our modeling results demonstrate significantly moderate to strong correlations between specific SPHARM coefficients and breast shape descriptors, such as height, width, projection, and ptosis. We employ these correlations to evaluate breast shape across several subjects and to interactively modify breast shape through these coefficients. We tested the robustness of our method to convert breast image data to SPHARM models and performed classification using the SPHARM coefficients on two types of breast reconstructions: transverse rectus abdominis myocutaneous (TRAM) flap reconstruction and implant reconstruction. Additionally, results were shown on predicting reconstructed breasts from SPHARM models based on preoperative breasts. Contributions of this research: A parametric breast model was developed that can (1) accurately and compactly represent breast data with a set of coefficients (shape descriptors), (2) easily adjust breast shape through modeled coefficients, (3) employ modeling approach to evaluate and differentiate different breast shapes, (4) generate template shape models representative of specific breast shape types, (5) perform classification using the SPHARM description, and (6) perform predictive modeling.