Learning U-Net Based Multi-Scale Features in Encoding-Decoding for MR Image Brain Tissue Segmentation.

Accurate brain tissue segmentation of MRI is vital to diagnosis aiding, treatment planning, and neurologic condition monitoring. As an excellent convolutional neural network (CNN), U-Net is widely used in MR image segmentation as it usually generates high-precision features. However, the performance of U-Net is considerably restricted due to the variable shapes of the segmented targets in MRI and the information loss of down-sampling and up-sampling operations.

[Preliminary construction of three-dimensional visual educational system for clinical dentistry based on world wide web webpage].

Objective: To establish a new visual educational system of virtual reality for clinical dentistry based on world wide web (WWW) webpage in order to provide more three-dimensional multimedia resources to dental students and an online three-dimensional consulting system for patients.

Methods: Based on computer graphics and three-dimensional webpage technologies, the software of 3Dsmax and Webmax were adopted in the system development. In the Windows environment, the architecture of whole system was established step by step, including three-dimensional model construction, three-dimensional scene setup, transplanting three-dimensional scene into webpage, reediting the virtual scene, realization of interactions within the webpage, initial test, and necessary adjustment.

[The application of artificial neural networks to predict individual risk of essential hypertension].

Objective: To establish models to predict individual risk of essential hypertension and to evaluate and explore new forecasting methods.

Methods: To select data of 3054 community residents from an epidemiological survey and divided them into 4:1 (2438 cases and 616 cases) ratio in accordance with the balance of age and sex to filter variables, and to establish, test and evaluate the prediction models. Using artificial neural network (ANN) and logistic regression analysis to establish models while applying ROC to evaluate the prediction models.