METHODS FOR PROCESSING 3D IMAGES FOR BREAST MORPHOLOGY

In this research, two novel algorithms are developed to facilitate quantitative evaluation of breast aesthetics for preoperative planning and postoperative outcome assessment in breast reconstruction surgery in cancer patients. First, an algorithm is presented for registering 3D images of individual patients from multiple clinical visits. Registration is performed to eliminate differences in object coordinate systems between images due to variations in patient positioning and posture, thereby facilitating longitudinal comparison of morphological changes in the reconstructed breasts. Second, an algorithm to detect from 3D images the lowest breast contour, an important attribute for breast aesthetics, is presented. The algorithm allows detection of the lowest breast contour, for ptosis grades of 0, 1, 2, and 3. Most importantly, the algorithm operates independent of the presence of fiducial points such as the nipple, making it robust for applicability to images of breasts at intermediate time points during reconstructive surgery that are devoid of nipples.

The applicability of the two algorithms is demonstrated in a multi-view 3D data fusion technique for visualization of the inframammary fold (IMF) in upright images from women with ptotic breasts. The IMF, a critical landmark for breast surgery and morphometry, is typically occluded for ptotic breasts in upright images, which is conventionally used for evaluation of breast aesthetics. Multi-view 3D images taken at two different positions (upright and supine) are employed in a data fusion approach to superimpose the IMF position, on 3D images of women with ptotic breasts wherein only the lowest breast contour is visible.

Contributions of this research: (1) The registration algorithm is more effective for multiple-visit images than traditional registration methods. This algorithm outperforms existing ICP algorithms and is robust to variations in body mass index (BMI). (2) The lowest breast contour detection algorithm, which computes contours in 3D images directly, is more effective than current methods, which detect contours in 2D images. (3) Multi-view 3D data fusion technique is a first attempt to visualize the IMF in upright images for women with ptotic breasts, which enables physicians to visualize the IMF position in upright images of women with high breast ptosis degrees (≥2).