Visual Display Method And Realization Of CT Images Based On Android Platform

Visualization of medical images on Android and other mobile platforms will be a trend in the development of Medical visualization.At present,the CT image visualization technology on the computer platform has become mature,but the development of CT image visualization technology on the Andrews platform has just started.In order to facilitate doctors or patients to observe and detect cases in a more efficient way,there is a need to implement a visualization system based on the Android platform,which can load CT images in human-computer interaction and display them on Android mobile devices.Based on the above considerations,there is a need to implement a visualization system of CT images based on the Android platform.The rendering results of traditional visualization system can only be displayed on the computer to shows the information contained in the CT images,and then drag the mouse to achieve the three-dimensional display of CT images.In contrast,the system not only to display CT image information in the Android mobile device,but also more humane in the display.The deflection angle of the mobile device can be changed by the acceleration sensor or the finger touch,and the projection image of the three-dimensional CT image can be displayed in the same time.In order to complete the work of the above study.at first,this system use the morphological segmentation method to segment the parts of interest to generate the mask Raw data.Secondly,the moving cube algorithm is improved so that the algorithm can reconstruct the different parts of the Raw data of the mask.Thirdly,the data conversion and the calculation of the mean normal vector are carried out according to the inherent format of obj file.Finally,the generated medical obj model is loaded according to the relevant drawing principle of OpenGL ES 2.0 on the Andrews equipment.In order to make the display better,different bones are set in different colors and are illuminated while the medical model is loaded in this system.In addition,the doctor can touch the finger or use the three-axis acceleration sensor to randomly select the interesting projection images to observe the model.This experiment tested a number of different cases,the medical models generated by each case are well displayed on Android mobile devices and are capable of normal human-computer interaction.In addition,this system also analyzes and summarizes the relationship between the various data variables involved in this study.