Abstract
The medical procedures related with the Breast Cancer Conservative Treatment (BCCT) have evolved towards the usage of affordable and practical tools, along with the recent inclusion of volumetric information of the breast. A richer three-dimensional (3D) model of the female torso allows, for instance, improvement of the evaluation the aesthetic outcome of BCCT and the surgery planning. The standard 3D reconstruction methods often fail to model objects of interest using highly misaligned views. In this work, a Tessellation-based coarse registration method is proposed, based on robust keypoints extraction from RGB-D data using the Delaunay Triangulation (DT) principle. With this method, it is possible to reconstruct female torso data with detail using only 3 views, in feasible time. Structures such as the nipples and the breast contour were correctly reconstructed and a highly correlated with reference models.

Abstract
Breast cancer is one of the most common malignanciesaffecting women worldwide. However, despite its incidence trends have increased, the mortality rate has significantly decreased. The primary concern in any cancer treatment is the oncological outcome but, in the case of breast cancer, the surgery aesthetic result has become an important quality indicator for breast cancer patients. In this sense, an adequate surgical planning and prediction tool would empower the patient regarding the treatment decision process, enabling a better communication between the surgeon and the patient and a better understanding of the impact of each surgical option. To develop such tool, it is necessary to create complete 3D model of the breast, integrating both inner and outer breast data. In this review, we thoroughly explore and review the major existing works that address, directly or not, the technical challenges involved in the development of a 3D software planning tool in the field of breast conserving surgery. © 2018 by Begell House, Inc.

Abstract
Three-dimensional imaging techniques have been endeavouring at reaching affordable ubiquity. Nevertheless, its use in clinical practice can be hampered by less than naturally looking surfaces that greatly impact its visual inspection. This work considers the task of surface reconstruction from point clouds of non-rigid scenes acquired through structured-light-based methods, wherein the reconstructed surface contains some level of imperfection to be inpainted before visualized by experts in a clinically oriented context. Appertain to the topic, the recovery of colour information for missing or damaged partial regions is considered. A local geometry-based interpolation method is proposed for the reconstruction of the bare human torso and compared against a reference differential equations based inpainting method. Widely used perceptual distance-based metrics, such as PSNR, SSIM and MS-SSIM, and the evaluation from a panel of experienced breast cancer surgeons is presented for the discussion on inpainting quality assessment.

Abstract
Introduction: Breast volume estimation is considered crucial for breast cancer surgery planning. A single, easy, and reproducible method to estimate breast volume is not available. This study aims to evaluate, in patients proposed for mastectomy, the accuracy of the calculation of breast volume from a low-cost 3D surface scan (Microsoft Kinect) compared to the breast MRI and water displacement technique. Material and Methods: Patients with a Tis/T1-T3 breast cancer proposed for mastectomy between July 2015 and March 2017 were assessed for inclusion in the study. Breast volume calculations were performed using a 3D surface scan and the breast MRI and water displacement technique. Agreement between volumes obtained with both methods was assessed with the Spearman and Pearson correlation coefficients. Results: Eighteen patients with invasive breast cancer were included in the study and submitted to mastectomy. The level of agreement of the 3D breast volume compared to surgical specimens and breast MRI volumes was evaluated. For mastectomy specimen volume, an average (standard deviation) of 0.823 (0.027) and 0.875 (0.026) was obtained for the Pearson and Spearman correlations, respectively. With respect to MRI annotation, we obtained 0.828 (0.038) and 0.715 (0.018). Discussion: Although values obtained by both methodologies still differ, the strong linear correlation coefficient suggests that 3D breast volume measurement using a low-cost surface scan device is feasible and can approximate both the MRI breast volume and mastectomy specimen with sufficient accuracy. Conclusion: 3D breast volume measurement using a depth-sensor low-cost surface scan device is feasible and can parallel MRI breast and mastectomy specimen volumes with enough accuracy. Differences between methods need further development to reach clinical applicability. A possible approach could be the fusion of breast MRI and the 3D surface scan to harmonize anatomic limits and improve volume delimitation.