The aim of this study is to investigate the color change of different restoration thicknesses, backgrounds and resin cement colors on lithium disilicate and zirconium reinforced lithium silicate materials in vitro. In...The aim of this study is to investigate the color change of different restoration thicknesses, backgrounds and resin cement colors on lithium disilicate and zirconium reinforced lithium silicate materials in vitro. In this study, IPS emax CAD (LT C14) and Celtra Duo (LT C14) are used as full ceramic materials, and Variolink Esthetic LC (warm, neutral) used as resin cement and Tokuyama Estelite Sigma Quick (A3, A2) is used as composite materials. A total of 160 samples in the form of 40 pieces of 5 × 5 0.4 mm thick 40 pieces of 5 × 5 0.6 mm thick square discs from each of the all-ceramic materials in block form were obtained using a water jet device (DWJ1525-FA;Dardi International Corporation, Nanjing, China). Glass ceramic samples produced in 2 different thicknesses were cemented on 2 different backgrounds with 2 different resin types of cement. Color measurements of the samples before and after cementation were performed on a grey background with spectrophotometer Vita EasyShade V (Vita Zahnfabrik, Bad Sackingen, Germany) and color parameters (L*, a*, b*, ΔE) were calculated according to the CIE Lab (Commission Internationale de L’Eclairage) system. Average values for each group (ΔE) were not affected by ceramic type, material thickness, background color, resin cement color, and the interaction of these four variables (p > 0.05). When the triple interactions between the groups were examined, there were no statistically significant differences (p > 0.05). In the evaluation of pairwise interactions between two groups (material type-material thickness, material type-background color, and thickness of material-background interactions) statistically significant differences (p Implications: The material type, thickness, background and cement color used did not cause any statistically significant color change in lithium disilicate and zirconium-reinforced lithium silicate glass ceramic materials (p > 0.05).展开更多
针对彩色像景CAD技术中现有分色算法过程复杂,易产生多解等问题,对比RIP分色技术,并根据彩色像景CAD技术的特性以及织物实际生产工艺,提出了一种基于在HSI颜色空间内进行色彩饱和度压缩的彩色像景CAD映射、分色方法。该方法根据基色色...针对彩色像景CAD技术中现有分色算法过程复杂,易产生多解等问题,对比RIP分色技术,并根据彩色像景CAD技术的特性以及织物实际生产工艺,提出了一种基于在HSI颜色空间内进行色彩饱和度压缩的彩色像景CAD映射、分色方法。该方法根据基色色调角度,将被映射颜色分为多个映射区域进行映射、分色,算法过程简单易懂,且解决了多基色映射时的多解问题。在Jacket for MatLab环境下实现了该彩色像景CAD映射分色方法。实验结果证明,这种方法具有良好的分色效果,且Jacket中GPU计算的应用使得图像处理速度大幅提升,从而保证了远程交互式设计的实时性。展开更多
This study explores an automated framework to assist the recognition of hemorrhage traces and bleeding lesions in video streams of small bowel capsule endoscopy (SBCE). The proposed methodology aims to achieve fast im...This study explores an automated framework to assist the recognition of hemorrhage traces and bleeding lesions in video streams of small bowel capsule endoscopy (SBCE). The proposed methodology aims to achieve fast image control (<10 minutes), save valuable time of the physicians, and enable high performance diagnosis. A specialized elimination algorithm excludes all identical consecutive frames by utilizing the difference of gray levels in pixel luminance. An image filtering algorithm is proposed based on an experimentally calculated bleeding index and blood-color chart, which inspects all remaining frames of the footage and identifies pixels that reflect active or potential hemorrhage in color. The bleeding index and blood-color chart are estimated of the chromatic thresholds in RGB and HSV color spaces, and have been extracted after experimenting with more than 3200 training images, derived from 99 videos of a pool of 138 patients. The dataset has been provided by a team of expert gastroenterologist surgeons, who have also evaluated the results. The proposed algorithms are tested on a set of more than 1000 selected frame samples from the entire 39 testing videos, to a prevalence of 50% pathologic frames (balanced dataset). The frame elimination of identical and consecutive frames achieved a reduction of 36% of total frames. The best statistical performance for diagnosis of positive pathological frames from a video stream is achieved by utilizing masks in the HSV color model, with sensitivity up to 99%, precision 94.41% to a prevalence of 50%, accuracy up to 96.1%, FNR 1%, FPR 6.8%. The estimated blood-color chart will be clinically validated and used in feature extraction schemes supporting machine learning ML algorithms to improve the localization potential.展开更多
文摘The aim of this study is to investigate the color change of different restoration thicknesses, backgrounds and resin cement colors on lithium disilicate and zirconium reinforced lithium silicate materials in vitro. In this study, IPS emax CAD (LT C14) and Celtra Duo (LT C14) are used as full ceramic materials, and Variolink Esthetic LC (warm, neutral) used as resin cement and Tokuyama Estelite Sigma Quick (A3, A2) is used as composite materials. A total of 160 samples in the form of 40 pieces of 5 × 5 0.4 mm thick 40 pieces of 5 × 5 0.6 mm thick square discs from each of the all-ceramic materials in block form were obtained using a water jet device (DWJ1525-FA;Dardi International Corporation, Nanjing, China). Glass ceramic samples produced in 2 different thicknesses were cemented on 2 different backgrounds with 2 different resin types of cement. Color measurements of the samples before and after cementation were performed on a grey background with spectrophotometer Vita EasyShade V (Vita Zahnfabrik, Bad Sackingen, Germany) and color parameters (L*, a*, b*, ΔE) were calculated according to the CIE Lab (Commission Internationale de L’Eclairage) system. Average values for each group (ΔE) were not affected by ceramic type, material thickness, background color, resin cement color, and the interaction of these four variables (p > 0.05). When the triple interactions between the groups were examined, there were no statistically significant differences (p > 0.05). In the evaluation of pairwise interactions between two groups (material type-material thickness, material type-background color, and thickness of material-background interactions) statistically significant differences (p Implications: The material type, thickness, background and cement color used did not cause any statistically significant color change in lithium disilicate and zirconium-reinforced lithium silicate glass ceramic materials (p > 0.05).
文摘针对彩色像景CAD技术中现有分色算法过程复杂,易产生多解等问题,对比RIP分色技术,并根据彩色像景CAD技术的特性以及织物实际生产工艺,提出了一种基于在HSI颜色空间内进行色彩饱和度压缩的彩色像景CAD映射、分色方法。该方法根据基色色调角度,将被映射颜色分为多个映射区域进行映射、分色,算法过程简单易懂,且解决了多基色映射时的多解问题。在Jacket for MatLab环境下实现了该彩色像景CAD映射分色方法。实验结果证明,这种方法具有良好的分色效果,且Jacket中GPU计算的应用使得图像处理速度大幅提升,从而保证了远程交互式设计的实时性。
文摘This study explores an automated framework to assist the recognition of hemorrhage traces and bleeding lesions in video streams of small bowel capsule endoscopy (SBCE). The proposed methodology aims to achieve fast image control (<10 minutes), save valuable time of the physicians, and enable high performance diagnosis. A specialized elimination algorithm excludes all identical consecutive frames by utilizing the difference of gray levels in pixel luminance. An image filtering algorithm is proposed based on an experimentally calculated bleeding index and blood-color chart, which inspects all remaining frames of the footage and identifies pixels that reflect active or potential hemorrhage in color. The bleeding index and blood-color chart are estimated of the chromatic thresholds in RGB and HSV color spaces, and have been extracted after experimenting with more than 3200 training images, derived from 99 videos of a pool of 138 patients. The dataset has been provided by a team of expert gastroenterologist surgeons, who have also evaluated the results. The proposed algorithms are tested on a set of more than 1000 selected frame samples from the entire 39 testing videos, to a prevalence of 50% pathologic frames (balanced dataset). The frame elimination of identical and consecutive frames achieved a reduction of 36% of total frames. The best statistical performance for diagnosis of positive pathological frames from a video stream is achieved by utilizing masks in the HSV color model, with sensitivity up to 99%, precision 94.41% to a prevalence of 50%, accuracy up to 96.1%, FNR 1%, FPR 6.8%. The estimated blood-color chart will be clinically validated and used in feature extraction schemes supporting machine learning ML algorithms to improve the localization potential.
