Abstract:Accounting for 26% of all new cancer cases worldwide, breast cancer remains the most common form of cancer in women. Although early breast cancer has a favourable long-term prognosis, roughly a third of patients suffer from a suboptimal aesthetic outcome despite breast conserving cancer treatment. Clinical-quality 3D modelling of the breast surface therefore assumes an increasingly important role in advancing treatment planning, prediction and evaluation of breast cosmesis. Yet, existing 3D torso scanners are expensive and either infrastructure-heavy or subject to motion artefacts. In this paper we employ a single consumer-grade RGBD camera with an ICP-based registration approach to jointly align all points from a sequence of depth images non-rigidly. Subtle body deformation due to postural sway and respiration is successfully mitigated leading to a higher geometric accuracy through regularised locally affine transformations. We present results from 6 clinical cases where our method compares well with the gold standard and outperforms a previous approach. We show that our method produces better reconstructions qualitatively by visual assessment and quantitatively by consistently obtaining lower landmark error scores and yielding more accurate breast volume estimates.
Abstract:Breast cancer is the most prevalent cancer type in women, and while its survival rate is generally high the aesthetic outcome is an increasingly important factor when evaluating different treatment alternatives. 3D scanning and reconstruction techniques offer a flexible tool for building detailed and accurate 3D breast models that can be used both pre-operatively for surgical planning and post-operatively for aesthetic evaluation. This paper aims at comparing the accuracy of low-cost 3D scanning technologies with the significantly more expensive state-of-the-art 3D commercial scanners in the context of breast 3D reconstruction. We present results from 28 synthetic and clinical RGBD sequences, including 12 unique patients and an anthropomorphic phantom demonstrating the applicability of low-cost RGBD sensors to real clinical cases. Body deformation and homogeneous skin texture pose challenges to the studied reconstruction systems. Although these should be addressed appropriately if higher model quality is warranted, we observe that low-cost sensors are able to obtain valuable reconstructions comparable to the state-of-the-art within an error margin of 3 mm.