Histomorphometric analysis of histologic sections of normal and diseased bone samples,such as healing allografts and fractures,is widely used in bone research.However,the utility of traditional semi-automated methods ...Histomorphometric analysis of histologic sections of normal and diseased bone samples,such as healing allografts and fractures,is widely used in bone research.However,the utility of traditional semi-automated methods is limited because they are labor-intensive and can have high interobserver variability depending upon the parameters being assessed,and primary data cannot be re-analyzed automatically.Automated histomorphometry has long been recognized as a solution for these issues,and recently has become more feasible with the development of digital whole slide imaging and computerized image analysis systems that can interact with digital slides.Here,we describe the development and validation of an automated application（algorithm）using Visiopharm＇s image analysis system to quantify newly formed bone,cartilage,and fibrous tissue in healing murine femoral allografts in high-quality digital images of H＆E/alcian blue-stained decalcified histologic sections.To validate this algorithm,we compared the results obtained independently using OsteoMeasureTM and Visiopharm image analysis systems.The intraclass correlation coefficient between Visiopharm and OsteoMeasure was very close to one for all tissue elements tested,indicating nearly perfect reproducibility across methods.This new algorithm represents an accurate and labor-efficient method to quantify bone,cartilage,and fibrous tissue in healing mouse allografts.展开更多
The performance of detector limits the overall performance of laser ranging system. And the design of multi-hit detector is one of the feasible ways to promote the performance of detector. Currently, the segmentation ...The performance of detector limits the overall performance of laser ranging system. And the design of multi-hit detector is one of the feasible ways to promote the performance of detector. Currently, the segmentation method or the recursive method is commonly used to analyze the multi-hit detector model. To the best of our knowledge, this paper is the first to propose a combinatorial method to solve the multi-hit detector model from the perspective of discrete time. Then, universal formulas of total signal detection probability and the average count are deduced based on the Poisson distribution signal. Furthermore, analysis is made to figure out how the average count changes with different parameters, such as the dead time, gating time, rate intensity. As a result, for GM-APD, the multi-hit detector model is verified advantageously compared to the single-hit detector model in improving the average count theoretically. Meanwhile, a discrete step feature is presented when average count changes with dead time or the gating time, which is of great significance in gating time optimization.展开更多
基金funded by grants(1S10RR027340-01 and AR43510) to BFB,and (R01 DE019902,P30 AR061307 and P50 AR054041) to EMS,from the National Institutes of Health
文摘Histomorphometric analysis of histologic sections of normal and diseased bone samples,such as healing allografts and fractures,is widely used in bone research.However,the utility of traditional semi-automated methods is limited because they are labor-intensive and can have high interobserver variability depending upon the parameters being assessed,and primary data cannot be re-analyzed automatically.Automated histomorphometry has long been recognized as a solution for these issues,and recently has become more feasible with the development of digital whole slide imaging and computerized image analysis systems that can interact with digital slides.Here,we describe the development and validation of an automated application（algorithm）using Visiopharm＇s image analysis system to quantify newly formed bone,cartilage,and fibrous tissue in healing murine femoral allografts in high-quality digital images of H＆E/alcian blue-stained decalcified histologic sections.To validate this algorithm,we compared the results obtained independently using OsteoMeasureTM and Visiopharm image analysis systems.The intraclass correlation coefficient between Visiopharm and OsteoMeasure was very close to one for all tissue elements tested,indicating nearly perfect reproducibility across methods.This new algorithm represents an accurate and labor-efficient method to quantify bone,cartilage,and fibrous tissue in healing mouse allografts.
文摘The performance of detector limits the overall performance of laser ranging system. And the design of multi-hit detector is one of the feasible ways to promote the performance of detector. Currently, the segmentation method or the recursive method is commonly used to analyze the multi-hit detector model. To the best of our knowledge, this paper is the first to propose a combinatorial method to solve the multi-hit detector model from the perspective of discrete time. Then, universal formulas of total signal detection probability and the average count are deduced based on the Poisson distribution signal. Furthermore, analysis is made to figure out how the average count changes with different parameters, such as the dead time, gating time, rate intensity. As a result, for GM-APD, the multi-hit detector model is verified advantageously compared to the single-hit detector model in improving the average count theoretically. Meanwhile, a discrete step feature is presented when average count changes with dead time or the gating time, which is of great significance in gating time optimization.
