Objective To improve the fitness and initial fixation strength between the hip and bone and to optimize the shape of the prosthetic implants. Methods The cross-section of hip canal was automatically extracted by Image processing. By using taper curve fit,hypocurve predigesting and the curve of shape center fit, the parameters of long-short diameter and the curve of shape center were got to design the hip shape.CAD was adopted to analyze and evaluate the configuration of bone and shape of hip.The “peg-in-hole” was employed to optimize the shape of implant by the visual test of “Drawingout” in computer. Results 23.2% hip-bone average matching rate and 0.033% bone damage rate were presented by CAD analysis. The implant extraction path were validated visually and quantitatively by measuring the maximum amount of overlap in the path configuration. Conclusion The valuable method for prothsetic hip design was presented by the way of image processing,graphics design and optimizingdesign in this study.
Objective To observe the affection of optic nerve under acute ocular hypertension and the effect of protection of bFGF on optic nerve. Methods BSS was perfused into anterior chamber of rabbits to increase the intraocular pressure to cause retinal ischemia. A computer image analysis system was used to count the optic nerve axons.Eyes were intravitreally injected with bFGF and then the number of optic nerve axons of the normal rabbits,and hypertension with and without bFGE treatment groups were counted respectively. Results The number of optic nerve axons in ocular hypertension eyes was less than the normal eyes(P=0.00003).The bFGF treated eyes had more optic nerve axons than the controls(P=0.0078). Conclusions The acute ocular hypertension may cause the loss of the nerve axons,and bFGF may be effective in protecting optic nerve in acute ocular hypertension. (Chin J Ocul Fundus Dis,2000,16:94-96)
Purpose To identify and quantitatively evaluate age-related changes in the retinal pigment epithelium (RPE) and underlying Bruch is membrane and choroid in donor human eyes. Methods 36unpaired human eyes of varying age (3-39 years) from Caucasian donors were supplied by Manchester Eye Bank (UK) or National Disease Research Interchange (Philadephia,USA).Modified Masson is trichrome staining was used to illustrate age-related changes in RPE cell, Bruch is membrane thickness, and density of choriocapillaries and thickness of the choroid. Data were assessed using computer-aided quantitative morphometric analysis method. ResultsThe thickness of Bruch is membrane increased with age while there is a change in morphology of RPE cells including a decrease in number and RPE cell thickening with age. RPE cells decreased at a rate of 8 cells/mm2 middot; year, RPE cell height and thickness of Bruch is membrane increased at rates of 0.01(mu;m/year) and 0.02 (mu;m/year) respectively. The luminal area of choriocapillaries and the thickness of choroid showed no close relation with age. Conclusion RPE cell loss and thickening of Bruch is membrane and RPE cells may be the earlier and primary alteration with age. (Chin J Ocul Fundus Dis,2000,16:236-239)
Purpose To investigate the pattern of subretinal neovascular membrane(SRNVM)in central exudative chorioretinitis(CEC). Methods With the help of a PC microcomputer,we performed a quantitative measurement of SRNVM in 32 eyes of 32 patients with Rieger is CEC. Results SRNVM-optic disc area ratio were 0.1151plusmn;0.0842．The foveola was on the top of SRNVM in 7 cases．The other 25 of SRNVMs were scattered in macular area around foveola,and 2 of them were nasal to it．The distance between the edge of SRNVM and foveola was less than 175mu;m in 13 cases,175～300mu;m in 4 cases and more than 300mu;m in 15 cases． Conclusion To be compared with the previous data,the present results suggested that laser photocoagulation might be one of the most important therapies for SRNVM in Rieger is CEC． (Chin J Ocul Fundus Dis,1998,14:114-115)
Lung cancer is the most threatening tumor disease to human health. Early detection is crucial to improve the survival rate and recovery rate of lung cancer patients. Existing methods use the two-dimensional multi-view framework to learn lung nodules features and simply integrate multi-view features to achieve the classification of benign and malignant lung nodules. However, these methods suffer from the problems of not capturing the spatial features effectively and ignoring the variability of multi-views. Therefore, this paper proposes a three-dimensional (3D) multi-view convolutional neural network (MVCNN) framework. To further solve the problem of different views in the multi-view model, a 3D multi-view squeeze-and-excitation convolution neural network (MVSECNN) model is constructed by introducing the squeeze-and-excitation (SE) module in the feature fusion stage. Finally, statistical methods are used to analyze model predictions and doctor annotations. In the independent test set, the classification accuracy and sensitivity of the model were 96.04% and 98.59% respectively, which were higher than other state-of-the-art methods. The consistency score between the predictions of the model and the pathological diagnosis results was 0.948, which is significantly higher than that between the doctor annotations and the pathological diagnosis results. The methods presented in this paper can effectively learn the spatial heterogeneity of lung nodules and solve the problem of multi-view differences. At the same time, the classification of benign and malignant lung nodules can be achieved, which is of great significance for assisting doctors in clinical diagnosis.
As the most efficient perception system in nature, the perception mechanism of the insect (such as honeybee) antennae is the key to imitating the high-performance sensor technology. An automated experimental device suitable for collecting electrical signals (including antenna reaction time information) of antennae was developed, in response to the problems of the non-standardized experimental process, interference of manual operation, and low efficiency in the study of antenna perception mechanism. Firstly, aiming at the automatic identification and location of insect heads in experiments, the image templates of insect head contour features were established. Insect heads were template-matched based on the Hausdorff method. Then, for the angle deviation of the insect heads relative to the standard detection position, a method that calculates the angle of the insect head mid-axis based on the minimum external rectangle of the long axis was proposed. Eventually, the electrical signals generated by the antennae in contact with the reagents were collected by the electrical signal acquisition device. Honeybees were used as the research object in this study. The experimental results showed that the accuracy of template matching could reach 95.3% to locate the bee head quickly, and the deviation angle of the bee head was less than 1°. The distance between antennae and experimental reagents could meet the requirements of antennae perception experiments. The parameters, such as the contact reaction time of honeybee antennae to sucrose solution, were consistent with the results of the manual experiment. The system collects effectively antenna contact signals in an undisturbed state and realizes the standardization of experiments on antenna perception mechanisms, which provides an experimental method and device for studying and analyzing the reaction time of the antenna involved in biological antenna perception mechanisms.
The automatic segmentation of auricular acupoint divisions is the basis for realizing intelligent auricular acupoint therapy. However, due to the large number of ear acupuncture areas and the lack of clear boundary, existing solutions face challenges in automatically segmenting auricular acupoints. Therefore, a fast and accurate automatic segmentation approach of auricular acupuncture divisions is needed. A deep learning-based approach for automatic segmentation of auricular acupoint divisions is proposed, which mainly includes three stages: ear contour detection, anatomical part segmentation and keypoints localization, and image post-processing. In the anatomical part segmentation and keypoints localization stages, K-YOLACT was proposed to improve operating efficiency. Experimental results showed that the proposed approach achieved automatic segmentation of 66 acupuncture points in the frontal image of the ear, and the segmentation effect was better than existing solutions. At the same time, the mean average precision (mAP) of the anatomical part segmentation of the K-YOLACT was 83.2%, mAP of keypoints localization was 98.1%, and the running speed was significantly improved. The implementation of this approach provides a reliable solution for the accurate segmentation of auricular point images, and provides strong technical support for the modern development of traditional Chinese medicine.