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In this paper, we present a whole procedure for constructing 3D models of stone tools including scanning, data acquisition and surface reconstruction with hole-filling. The process of scanning hundreds or thousands of small objects is time consuming. Our original 3D laser scanner optimizes the scanning process and reduces time significantly by four directional scanning of many small objects simultaneously. To reconstruct surface of stone tools, the scanned point clouds are processed with a new triangulation method that preserves the properties of sharp edges. Our approach is based on a projection based method in which points are distinguished into neighboring layers with a point cloud slicing method to be individually reconstructed. In addition, we introduce a simple hole-filling algorithm for mesh completion of models. The main advantages of our approach are speed and efficiency for reconstruction of many small objects.

We established a multi-institution model (big model) of knowledge-based treatment planning with over 500 treatment plans from five institutions in volumetric modulated arc therapy (VMAT) for prostate cancer. This study aimed to clarify the efficacy of using a large number of registered treatment plans for sharing the big model. The big model was created with 561 clinically approved VMAT plans for prostate cancer from five institutions (A: 150, B: 153, C: 49, D: 60, and E: 149) with different planning strategies. The dosimetric parameters of planning target volume (PTV), rectum, and bladder for two validation VMAT plans generated with the big model were compared with those from each institutional model (single-institution model). The goodness-of-fit of regression lines (R2 and χ2 values) and ratios of the outliers of Cook’s distance (CD) > 4.0, modified Z-score (mZ) > 3.5, studentized residual (SR) > 3.0, and areal difference of estimate (dA) > 3.0 for regression scatter plots in the big model and single-institution model were also evaluated. The mean ± standard deviation (SD) of dosimetric parameters were as follows (big model vs. single-institution model): 79.0 ± 1.6 vs. 78.7 ± 0.5 (D50) and 0.13 ± 0.06 vs. 0.13 ± 0.07 (Homogeneity Index) for the PTV; 6.6 ± 4.0 vs. 8.4 ± 3.6 (V90) and 32.4 ± 3.8 vs. 46.6 ± 15.4 (V50) for the rectum; and 13.8 ± 1.8 vs. 13.3 ± 4.3 (V90) and 39.9 ± 2.0 vs. 38.4 ± 5.2 (V50) for the bladder. The R2 values in the big model were 0.251 and 0.755 for rectum and bladder, respectively, which were comparable to those from each institution model. The respective χ2 values in the big model were 1.009 and 1.002, which were closer to 1.0 than those from each institution model. The ratios of the outliers in the big model were also comparable to those from each institution model. The big model could generate a comparable VMAT plan quality compared with each single-institution model and therefore could possibly be shared with other institutions.

Hairstyles are important for many women in visual attractiveness. However, it is difficult to objectively judge by themselves which hairstyle suits for them. Previous study has reported that circular-based complexity of psychological potential field (PPF), which can be calculated on digital images, indicates goodness of impressions for facial shapes. In this paper, we apply some complexities of PPF, including the previous complexity, to facial images to investigate whether good hairstyles for facial impressions can be quantified. Here, with constraining several facial components, subjective evaluation and objective evaluation have been compared by correlation analysis. Subjective evaluation adopts a paired comparison method, and objective evaluation adopts several shape analyses of PPF produced from each facial image. The results show a necessity to evaluate PPF with the gender separated. Moreover, some three-dimensional complexities of PPF indicated a certain effectiveness to assess good impression for hairstyles.