Objective:To analyze the accuracy of the digital imaging fiber optic transillumination (DIFOTI) on diagnosis of caries lesions depth using DIAGNOcam system.Methods:This experiment adopted self-matching design.Seventy-four extracted teeth (molar:sixty-six,premolar:eight) with one caries lesions in proximity which were not damaged in surface marginal ridge were selected.Dental calculus and dental stains were removed from the extracted teeth for standby application.A sign was marked in the middle of the occlusal surface edge at the side of decay.Then the teeth were fixed in the standard model of dentition and cavities were adjacent with the sound tooth surface.Sticky wax was applied to seal the level of 2 mm beyond cemento-enamel junction (CEJ) in the direction of occlusion and interproximal space to imitate gingival margin and gingival papilla.The standard models of dentition was seated in imitation head mold.The lesions depth degree was looked into and checked with DIAGNOcam system.Besides,the pictures on the occlusal surfaces were recorded and saved.The sign above could be seen on the picture.The measuring tool in DIAGNOcam system was used to measure the depth of the caries from the sign (as starting point) to the deepest point of caries in the pictures and its length was recorded for a.The line a was lengthened to the contralateral edge of occlusal surface in the photo and the length was recorded for b.A line from the marked point on the occlusal surface edge of the extracted teeth was draw parallel to the line b on the corresponding photo and its length was recorded for c.The depth of the cavities on the projected images was recorded for d,and calculated d/a =c/b (digital optical fiber measured decay depth/caries damage depth of the image =actual tooth width/tooth width of the image),and d =c/b × a inferred.At last,the teeth were taken out from the standard model dentition.The decay of the tooth was removed completely.The actual depth of the cavity was recorded for D.The difference between d and D was recorded for Δd.The software of SPSS 20.0 was used to test the consistency of the results,and the MedCalc 14.8.1.0 software was used for Bland-Altman analysis.Results:The intraclass correlation coefficient (ICC) between d and D was 0.951 (ICC ＞ 75 ％),P =0.263.There was a function relationship y =0.23 ± 0.9 1x between d (x) and D (y).Bland-Altman analysis method showed that the mean of Δd (Δd) was 0.05 mm,the standard deviation of Δd (ΔdsD) =0.308,and the 95％ confidence interval was (-0.55 to 0.65).The amplitude of difference was clinically acceptable.So the consistency of the two measurement modes was high.Conclusion:There was no significant difference between the depth of caries lesions checked with DIAGNOcam system and the depth of the actual cavity,and the consistency was very good.The vitro study suggests that the DIAGNOcam system may be used to assess the depth of caries cavity as a useful tool in diagnosis and treatment.

Objective To improve the key steps of direct volume rendering(DVR) method to obtain ideal semitransparent 3D visualization of medical images from 2D slices.Method An arbitrary data set was classified into a simple one and a complex one according to the boundaries existing within the data set,thereby a piecewise linear function was used to construct the transfer function(TF).Low-grayed voxels were regarded as a kind of material which did not radiate but do induce attenuation of sampling lights.The TF was adjusted according to the opacity distribution when one resampling process ends,and the rendering procedure was completed.Result Interior structures of tissues in different levels were rendered.Conclusion Multi-level visualization of 3D medical images for the semitransparent effect can be obtained by considering all the tissues in the data set as semitransparent materials.

Speckle is the main reason which declines the quality of medical ultrasonic images. In this paper, the initial condition for the Downhill filter, a morphological reconstruction algorithm, is modified and applied in the speckle reduction. Firstly, the initial area and start position as the mark image was determined in the marker image. Then the modified Downhill filter was used in the ultrasonic marker image. The results showed that, in comparison with the other three filters, this modified Downhill filter, while maintaining the integrity of the contour,could reduce the speckle in the regions of cavity efficiently and rapidly.
Algorithms ; Humans ; Image Enhancement ; methods ; Image Processing, Computer-Assisted ; Ultrasonography ; methods

Lower contrast and speckle noise are the main reasons which decline the quality of medical ultrasonic images. In this paper, a new method is proposed to filter the speckle noises and enhance the contrast simultaneously. Anisotropic diffusion filtering method was firstly applied to filter images. Then the loss of information, which the contrast function of contrast enhancement model lies on, was obtained. Finally, the contrast can be enhanced by using enhancement model. Experimental results show that the proposed method not only removes the speckle noises effectively, but also enhances the contrast obviously. This method supplies an effective approach for improving the quality of medical ultrasonic images.
Algorithms ; Anisotropy ; Humans ; Image Enhancement ; Image Processing, Computer-Assisted ; methods ; Signal Processing, Computer-Assisted ; Ultrasonography ; methods

Objective To improve the precision of the traditional segmentation of echocardiogram, by suppressing the influence from inherent speckle noises in medical ultrasonic images. Method An automatic segmentation method based on reconstructed morphology was proposed in this paper. First, the opening and closing operations by reconstruction were imposed to the ultrasonic image. Second, the top-hat operation was used to extract the bright and/or dark features and to find out the boundaries corresponding to these features, whereby implemented the automatic segmentation. Result The segmented echocardiogram had less artificial boundaries resulted from speckle noise, and could accurately be extracted the artery and ventricle. Conclusion The presented method can detect both dark and bright objects accurately, and the boundary has a fine continuity. In addition, the algorithm is also applicable to the extraction of sole bright/dark features, accordingly to reduce the complexity and time needed and to improve the accuracy.

Objective To compare the kinematics of the knee joint of normal Chinese people and people after fixed-bearing posterior stabilized total knee arthroplasty while doing weight-bearing deep knee-bending using fluoroscopy analysis.Methods From June to December 2010,ten volunteers and ten patients with fixed-bearing posterior stabilized total knee arthroplasty (TKA) were required to perform weight-bearing deep knee-bending activity under surveillance of roentgenization,motion between femur and tibia was analyzed with interval of 15° according to two-to three-dimensional (2D-3D) registration technique.Results During weight-bearing deep knee-bending,the average weight-bearing maximal flexion was 136° in the normal group,which was significantly higher than the 125° in the TKA group.All 10 normal knees present posterior translation of femoral condyle during deep knee-bending,posterior translation of the lateral condyle was greater than medial condyle,thereby creating a medial pivot type of axial rotational pattern in which the tibia internally rotates relative to the femur as flexion increased.The average amount of posterior femoral translation of the medial condyle was 7.3±1.2 mm,whereas the lateral condyle translated posteriorly 19.3±3.1 mm.All knees experienced tibia rotated internally during progressive flexion,and the average amount of axial rotation for the ten subjects from 0° to 135° was 23.8±3.4°.From extension to maximal flexion,the average amount of posterior translation of medial condyle was 1.4±0.6 rmm,whereas the lateral condyle translated 6.4±1.7 mm in the posterior direction in the fixed-bearing posterior-stabilized TKA.The average amount of tibial internal rotation was 8.5°±3.4°.Conclusion In normal Chinese people,during knee flexion activities the lateral condyle experiences significantly more amount of posterior translation than the medial condyle,leading to the tibia present medial pivot internal rotation relative to the femur,and the PFC-Sigrna fixed-bearing posterior stabilized designs has the similar kinematics with normal knee,but the posterior condylar translation and tibial axial rotation are much less than the normal.

A method based on a symmetric region growing algorithm is presented for the segmentation of ultrasonic medical image. The method divides into three steps. First, according to the characteristic of the ultrasonic medical images, an adaptive weighted median filter is used to suppress speckle noise. Then, scan the digital image from the first row and grow regions from each scanned point by applying the growth criteria and combination criteria until all image pixels have been scanned. Examine the resulting regions using the seed criteria. If any point of a region satisfies the criteria for the region of interest region, assign the region to the resulting segmented image. The effectiveness of this method and a group of growth criteria as well as combination criteria applicable to ultrasonic medical image have been obtained by cardiac ultrasound image segmentation experiments. The experiment result shows that this method is good in the performance of the segmention of cardiac ultrasonic medical image.
Algorithms ; Echocardiography ; methods ; Humans ; Image Enhancement ; methods ; Image Processing, Computer-Assisted

This study aims to provide a computer-aided method for the diagnosis of fatty liver by B-scan ultrasonic imaging. Fatty liver is referred to the infiltration of triglycerides and other fats of the liver cells, which affected the texture of liver tissue. In this paper, some features including mean intensity ratio, as well as angular second moment, entropy and inverse differential moment of gray level co-occurrence matrix were extracted from B-scan ultrasonic liver images. Feature vectors which indicated two classes of images were created with the four features. Then we used kappa-means clustering algorithm, self-organized feature mapping (SOFM) artificial neural network and back-propagation (BP) artificial neural network to classify these vectors. The accuracy rate of kappa-means clustering algorithm was 100% for normal liver and 63.6% for fatty liver. The results of SOFM neural network showed that the accuracy rate was 84.8% for normal liver and 90.9% for fatty liver. The accuracy rate of neural network was 100% both for normal liver and fatty liver. This technology could detect the characteristics of B-scan images of normal liver and fatty liver more accurately. It could greatly improve the accuracy of the diagnosis of fatty liver.
Diagnosis, Differential ; Fatty Liver ; diagnostic imaging ; Humans ; Image Processing, Computer-Assisted ; methods ; Lung ; diagnostic imaging ; Neural Networks (Computer) ; Sensitivity and Specificity ; Ultrasonography

To solve the problem of imprecise positioning of feature point and of the feature data redundancy in facial expression recognition by active appearance models (AAM), the automatic adjustment of initial model for AAM fitting is proposed in this paper. The specific aims are to improve the precision of positioning and to more effectively reflect the variation of expressions by acquired features. The problem of feature selection is resolved by adopting quadratic mutual information and reducing the feature dimension. The support vector machine (SVM) classifier is used for expression recognition. The experimental results on CAS-PEAL facial expression database show that the proposed method effectively improves the performance of facial expression recognition, the maximum recognition rate being 83.33%.
Algorithms ; Computer Simulation ; Facial Expression ; Humans ; Image Interpretation, Computer-Assisted ; methods ; Models, Biological ; Pattern Recognition, Automated ; methods ; Signal Processing, Computer-Assisted

The ultrasonic estimation of fetal weight at delivery is of important prognostic significance in obstetrical practice. The convertional regression formulas used for estimating fetal weight have the disadvantage of less reliability. In this study, we used the back propagation neural network (BP) to estimate Fetal Weight. Some input variables were adopted in constructing the BP model: biparietal diameter (BPD), cerebellum transverse diameter (TCD), abdominal circumference (AC), liver length (LL), femur length (FL), fetal thigh soft tissue thickness (FSTT), and gestational age (GA). The fetal weights of 109 singleton fetuses were estimated. In the training group and validation group, coincidence rates were 89.77% and 76.19% respectively. The results show that the estimation based on neural network is more accurate than that by regression method. GA, its unit is not week but day in our formulas, is very valuable in combination with other ultrasonic parameters on estimation.
Anthropometry ; methods ; Birth Weight ; Female ; Fetal Weight ; Gestational Age ; Humans ; Infant, Newborn ; Neural Networks (Computer) ; Pregnancy ; Regression Analysis ; Term Birth