The DNA content and morphometric features of hepatocellular carcinoma (HCC) and liver cell dysplasia (LCD), including nuclear area, nuclear perimeter, nuclear maximum diameter and nuclear circle diameter, were quantit...The DNA content and morphometric features of hepatocellular carcinoma (HCC) and liver cell dysplasia (LCD), including nuclear area, nuclear perimeter, nuclear maximum diameter and nuclear circle diameter, were quantitatively determined by means of image analysis technology. The results showed that in comparison with normal hepatocytes, LCD had a markedly increased DNA content and nuclear morphometric parameters, but the values were lower than those for HCC. LCD showed a slight increase in nuclear atypia represented by the nuclear irregular index, which was also less than HCC. The findings indicate that LCD may be a precaneerous lesion of HCC, to the cells in an abnormal proliferative state.展开更多
Gifted children are able to learn in a more advanced way than others, probably due to neurophysiological differences in the communication efficiency in neural pathways. Topological features contribute to understanding...Gifted children are able to learn in a more advanced way than others, probably due to neurophysiological differences in the communication efficiency in neural pathways. Topological features contribute to understanding the correlation between the brain structure and intelligence. Despite decades of neuroscience research using MRI, methods based on brain region connectivity patterns are limited by MRI artifacts, which therefore leads to revisiting MRI morphometric features, with the aim of using them to directly identify gifted children instead of using brain connectivity. However, the small, high-dimensional morphometric feature dataset with outliers makes the task of finding good classification models challenging. To this end, a hybrid method is proposed that combines tensor completion and feature selection methods to handle outliers and then select the discriminative features. The proposed method can achieve a classification accuracy of 93.1%, higher than other existing algorithms, which is thus suitable for the small MRI datasets with outliers in supervised classification scenarios.展开更多
Lunar landforms are the results of geological and geomorphic processes on the lunar surface.It is very important to identify the types of lunar landforms.Geomorphology is the scientific study of the origin and evoluti...Lunar landforms are the results of geological and geomorphic processes on the lunar surface.It is very important to identify the types of lunar landforms.Geomorphology is the scientific study of the origin and evolution of morphological landforms on planetary surfaces.Elevation and relief amplitude are the most commonly used geomorphic indices in geomorphological classification studies.Previous studies have determined the elevation classification criteria of the lunar surface.In this paper,we focus on the classification criteria of the topographic relief amplitude of the lunar surface.To estimate the optimal window for calculating the relief amplitude of the lunar surface,we use the mean change-point method based on LOLA(Lunar Orbiter Laser Altimeter)Digital Elevation Model(DEM)data and SLDEM2015 DEM data combining observations from LOLA and SELenological and Engineering Explorer Terrain Camera(SELENE TC).The classification criterion of the lunar surface relief amplitude is then determined according to the statistical analysis of basic lunar landforms.Taking the topographic relief amplitudes of 100 m,200 m,300 m,700 m,1500 m and 2500 m as thresholds,the lunar surface is divided into seven geomorphic types,including minor microrelief plains(<100 m),minor microrelief platforms[100 m,200 m),microrelief landforms[200 m,300 m),small relief landforms[300 m,700 m),medium relief landforms[700 m,1500 m),large relief landforms[1500 m,2500 m)and extremely large relief landforms(≥2500 m).The minor microrelief plains are mainly distributed in the maria and the basalt filled floors of craters and basins,while the minor microrelief platforms are mainly in the transition regions between the maria and highlands.The microrelief landforms are mainly located in regions with relatively high topography,such as wrinkle ridges and sinuous rilles in the mare.The small relief landforms are mainly scattered in the central peak and floor fractures of craters.The medium relief landforms are mainly distributed in the transition regions between crater floors and crater walls,between crater walls and crater rims,between basin floors and basin walls,and between basin walls and basin rims.Large and extremely large relief landforms are mainly found along crater walls and basin walls.The classification criteria determination for assessing lunar surface relief amplitude described in this paper can provide important references for the construction of digital lunar surface geomorphology classification schemes.展开更多
文摘The DNA content and morphometric features of hepatocellular carcinoma (HCC) and liver cell dysplasia (LCD), including nuclear area, nuclear perimeter, nuclear maximum diameter and nuclear circle diameter, were quantitatively determined by means of image analysis technology. The results showed that in comparison with normal hepatocytes, LCD had a markedly increased DNA content and nuclear morphometric parameters, but the values were lower than those for HCC. LCD showed a slight increase in nuclear atypia represented by the nuclear irregular index, which was also less than HCC. The findings indicate that LCD may be a precaneerous lesion of HCC, to the cells in an abnormal proliferative state.
基金This work was supported by the National Key R&D Program of China(Grant No.2017YFE0129700)the National Natural Science Foundation of China(Key Program)(Grant No.11932013)+4 种基金the National Natural Science Foundation of China(Grant No.61673224)the Tianjin Natural Science Foundation for Distinguished Young Scholars(Grant No.18JCJQJC46100)the Tianjin Science and Technology Plan Project(Grant No.18ZXJMTG00260)based upon work from COST Action CA18106,supported by COST(European Cooperation in Science and Technology)supported by grants PICT 2017-3208 and UBACYT 20020170100192BA(Argentina)。
文摘Gifted children are able to learn in a more advanced way than others, probably due to neurophysiological differences in the communication efficiency in neural pathways. Topological features contribute to understanding the correlation between the brain structure and intelligence. Despite decades of neuroscience research using MRI, methods based on brain region connectivity patterns are limited by MRI artifacts, which therefore leads to revisiting MRI morphometric features, with the aim of using them to directly identify gifted children instead of using brain connectivity. However, the small, high-dimensional morphometric feature dataset with outliers makes the task of finding good classification models challenging. To this end, a hybrid method is proposed that combines tensor completion and feature selection methods to handle outliers and then select the discriminative features. The proposed method can achieve a classification accuracy of 93.1%, higher than other existing algorithms, which is thus suitable for the small MRI datasets with outliers in supervised classification scenarios.
基金Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDB41000000National Natural Science Foundation of China,No.42130110,No.41571388Key Project of National Basic Work of Science and Technology,No.2015FY210500。
文摘Lunar landforms are the results of geological and geomorphic processes on the lunar surface.It is very important to identify the types of lunar landforms.Geomorphology is the scientific study of the origin and evolution of morphological landforms on planetary surfaces.Elevation and relief amplitude are the most commonly used geomorphic indices in geomorphological classification studies.Previous studies have determined the elevation classification criteria of the lunar surface.In this paper,we focus on the classification criteria of the topographic relief amplitude of the lunar surface.To estimate the optimal window for calculating the relief amplitude of the lunar surface,we use the mean change-point method based on LOLA(Lunar Orbiter Laser Altimeter)Digital Elevation Model(DEM)data and SLDEM2015 DEM data combining observations from LOLA and SELenological and Engineering Explorer Terrain Camera(SELENE TC).The classification criterion of the lunar surface relief amplitude is then determined according to the statistical analysis of basic lunar landforms.Taking the topographic relief amplitudes of 100 m,200 m,300 m,700 m,1500 m and 2500 m as thresholds,the lunar surface is divided into seven geomorphic types,including minor microrelief plains(<100 m),minor microrelief platforms[100 m,200 m),microrelief landforms[200 m,300 m),small relief landforms[300 m,700 m),medium relief landforms[700 m,1500 m),large relief landforms[1500 m,2500 m)and extremely large relief landforms(≥2500 m).The minor microrelief plains are mainly distributed in the maria and the basalt filled floors of craters and basins,while the minor microrelief platforms are mainly in the transition regions between the maria and highlands.The microrelief landforms are mainly located in regions with relatively high topography,such as wrinkle ridges and sinuous rilles in the mare.The small relief landforms are mainly scattered in the central peak and floor fractures of craters.The medium relief landforms are mainly distributed in the transition regions between crater floors and crater walls,between crater walls and crater rims,between basin floors and basin walls,and between basin walls and basin rims.Large and extremely large relief landforms are mainly found along crater walls and basin walls.The classification criteria determination for assessing lunar surface relief amplitude described in this paper can provide important references for the construction of digital lunar surface geomorphology classification schemes.
