This paper introduces the hardware and software of a biomechanical robot-based testing device. The bottom control orders, posture and torque data transmission, and the control algorithms are integrated in a unified visual control platform by Visual C+ +, with easy control and management. By using hybrid force-displacement control method to load the human spine, we can test the organizational structure and the force state of the FSU (Functional spinal unit) well, which overcomes the shortcomings due to the separation of the force and displacement measurement, thus greatly improves the measurement accuracy. Also it is esay to identify the spinal degeneration and the load-bearing impact on the organizational structure of the FSU after various types of surgery.
Algorithms ; Biomechanical Phenomena ; Equipment Design ; Humans ; Joints ; physiology ; Robotics ; instrumentation ; methods ; Software ; Spine ; physiology

A Fast Multi-resolution Volume Rendering Method (FMVRM) based on wavelet and Shear-Warp is herein proposed. In this method, the medical volume data is compressed using wavelet transformation first. Then based on the set resolution, the medical volume data is decompressed guided by Opacity transfer function (OTF). Finally, the 3D medical image is reconstructed on the basis of Shear-Warp using Block-based run length encoded (BRLE) data structure, in which, the aliasing artifacts resulting from under-sampling in Shear-Warp is avoided by the pre-integrated volume rendering technology. Experiments demonstrate the good performance of the proposed method.
Algorithms ; Artifacts ; Data Compression ; methods ; Humans ; Imaging, Three-Dimensional ; methods

Limited by the imaging principle of whole body bone SPECT image, the gray value of bladder area is quite high, which affects the image's brightness, contrast and readability. In the meantime, the similarity between bladder area and focus makes it difficult for some images to be segmented automatically. In this paper, an improved Snake model, GVF Snake, is adopted to automatically segment bladder area, preparing for further processing of whole body bone SPECT images.
Algorithms ; Bone and Bones ; diagnostic imaging ; Humans ; Image Processing, Computer-Assisted ; Models, Anatomic ; Tomography, Emission-Computed, Single-Photon ; methods ; Urinary Bladder

Based on the characteristic of the PET-CT multimodal image series, a novel image registration and fusion method is proposed, in which the cubic spline interpolation method is applied to realize the interpolation of PET-CT image series, then registration is carried out by using mutual information algorithm and finally the improved principal component analysis method is used for the fusion of PET-CT multimodal images to enhance the visual effect of PET image, thus satisfied registration and fusion results are obtained. The cubic spline interpolation method is used for reconstruction to restore the missed information between image slices, which can compensate for the shortage of previous registration methods, improve the accuracy of the registration, and make the fused multimodal images more similar to the real image. Finally, the cubic spline interpolation method has been successfully applied in developing 3D-CRT (3D Conformal Radiation Therapy) system.
Algorithms ; Artificial Intelligence ; Diagnostic Imaging ; methods ; Humans ; Image Enhancement ; instrumentation ; methods ; Image Interpretation, Computer-Assisted ; instrumentation ; methods ; Imaging, Three-Dimensional ; instrumentation ; methods ; Pattern Recognition, Automated ; methods ; Positron-Emission Tomography ; instrumentation ; methods ; Radiotherapy Planning, Computer-Assisted ; instrumentation ; methods ; Tomography, X-Ray Computed ; instrumentation ; methods

Multi-modal medical image fusion has important value in clinical diagnosis and treatment. In this paper, the multi-resolution analysis of Daubechies 9/7 Biorthogonal Wavelet Transform is introduced for anatomical and functional image fusion, then a new fusion algorithm with the combination of local standard deviation and energy as texture measurement is presented. At last, a set of quantitative evaluation criteria is given. Experiments show that both anatomical and metabolism information can be obtained effectively, and both the edge and texture features can be reserved successfully. The presented algorithm is more effective than the traditional algorithms.
Algorithms ; Artificial Intelligence ; Diagnostic Imaging ; methods ; Humans ; Image Enhancement ; methods ; Image Interpretation, Computer-Assisted ; methods ; Image Processing, Computer-Assisted ; methods ; Pattern Recognition, Automated ; methods ; Positron-Emission Tomography ; methods ; Tomography, X-Ray Computed ; methods

In order to improve the effect and efficiency of the reconstructed image after hybrid volume rendering of different kinds of volume data from medical sequential slices or polygonal models, we propose a hybrid volume rendering method based on Shear-Warp with economical hardware. First, the hybrid volume data are pre-processed by Z-Buffer method and RLE (Run-Length Encoded) data structure. Then, during the process of compositing intermediate image, a resampling method based on the dual-interpolation and the intermediate slice interpolation methods is used to improve the efficiency and the effect. Finally, the reconstructed image is rendered by the texture-mapping technology of OpenGL. Experiments demonstrate the good performance of the proposed method.
Algorithms ; Computer Graphics ; Image Processing, Computer-Assisted ; methods ; Medical Illustration ; Models, Anatomic ; Phantoms, Imaging

In this paper, BP neural network is used to segment whole body bone SPECT image so that the lesion area can be recognized automatically. For the uncertain characteristics of SPECT images, it is hard to achieve good segmentation result if only the BP neural network is employed. Therefore, the segmentation process is divided into three steps: first, the optimal gray threshold segmentation method is employed for preprocessing, then BP neural network is used to roughly identify the lesions, and finally template match method and symmetry-removing program are adopted to delete the wrongly recognized areas.
Algorithms ; Bone and Bones ; diagnostic imaging ; Humans ; Image Interpretation, Computer-Assisted ; methods ; Neural Networks (Computer) ; Pattern Recognition, Automated ; methods ; Tomography, Emission-Computed, Single-Photon ; Whole Body Imaging

Objective:To evaluate the effect of uncoupling protein 1 (UCP1) expression of perirenal fat on the prognosis of clear cell renal cell carcinoma (ccRCC) .Methods:From Feb. 2013 to Oct. 2013 and Mar. 2015 to Oct. 2015, 98 patients with ccRCC who underwent retroperitoneal laparoscopic radical nephrectomy were analyzed. UCP1 mRNA of perirenal fat around tumor was detected by RT-qPCR. Preoperative Computed tomography (CT) images were used to evaluate the thickness and adhesiveness of perirenal fat. According to the UCP1 mRNA value, the patients were divided into high UCP1 group (42 cases) and low UCP1 group (56 cases) . The general clinical data, perirenal fat thickness and adhesiveness were compared, and Kaplan Meier curve was used to evaluate the difference of progression free survival (PFS) between the two groups. Univariate and multivariate Cox analysis were used to determine the potential independent prognostic factors of PFS.Results:In the high UCP1 group, the renal fat thickness, the ratio of fat adhesion, the ratio of Ⅲ to Ⅳ in Fuhrman grade and the ratio of >T2 in T stage were higher than those in the low UCP1 group[ (13.84±2.41) vs (10.75±1.99) , 42.86% vs 16.07%, 28.57% vs 8.93%, 21.43% vs. 5.36%; P=0.000, P=0.003, P=0.011, P= 0.037]. During the follow-up period (median, 62.0 months) , 15 cases (12 cases of high UCP1 group, 3 case of low UCP1 group) developed tumor progression. Kaplan Meier curve showed that PFS of high UCP1 group was worse than that of low UCP1 group (71.43% vs 94.64%, P=0.001) . Cox regression analysis showed that high UCP1 expression and high T stage were significantly correlated with low PFS ( β=1.334, RR=3.796, 95% CI=1.009-14.280, P= 0.048; β=2.886, RR=17.930, 95% CI=5.538-58.047, P=0.000) . Conclusions:The increased UCP1 expression of perirenal fat may be an independent risk factor of tumor progression in ccRCC. Combined with the assessment of browning of perirenal adipose tissue may be helpful for risk stratification of ccRCC patients after surgery.