3D breast surface reconstructions from consumer-grade RGB-D cameras

Abstract

Breast cancer is one of the most prevalent yet increasingly treatable cancer types. Clinical studies are suggesting a significant impact of breast cancer treatment on female patients' wellbeing and quality of life. With the oncological prognosis for mastectomy being on par with breast-conserving surgery, the latter still does lead to poor or suboptimal results in nearly a third of cases. Geometric 3D models of the breast have the potential to aid planning, assessment and prediction of treatment but require sustaining costly infrastructure-heavy commercial scanning solutions. This cross-disciplinary work within the scope of a European project investigates recently marketed depth consumer cameras as low-cost easy-to-operate imaging devices for dense 3D breast surface reconstruction. Clinical data acquisition software in accordance with a predefined protocol is implemented and deployed. Preliminary breast surface models from extending a state-of-the-art static-scene reconstruction method are validated on synthetic, phantom and clinical data. Contemporary publicly available reconstruction frameworks from the computer vision and robotics community are subsequently evaluated. Their shortcomings with respect to the characteristics of the captured breast data are addressed in a new tailored non-rigid reconstruction pipeline. Favourable accuracy and precision are underpinned by an extensive clinical data validation including a breast volume comparison study against the gold standard.