Infinitesimal nonrigidity of convex surfaces with planar boundary

In the present paper infinitesimal nonrigidity of a class of convex surfaces with planar boundary is given. This result shows that if the image of the Gauss map of an evolution convex surface with planar boundary covers some hemisphere, this surface may be of infinitesimal nonrigidity for the isometric deformation of planar boundary.

Theoretical Exploration of Stereochemical Nonrigidity for RfCo（PF3）x（CO）4-x（Rf=CF3, C2F5, C3F7, x=0-4）

The stereochemical nonrigidity of RfCo（PF3）x（CO）4-x（Rf=CF3,C2F5,C3F7,x=0-4） was studied at the theoretical level of B3LYP/6-31 1＋G^＊ via Gaussian 09.The intramolecular rearrangements in these penta-coordinated compounds are mainly caused by the vibrations of perfluoroalkyl groups.All the barriers along the reaction coordinate are less than 66.9 kJ/mol,which indicates that the rearrangements are kinetically favorable and hard to elucidate by experiment.Besides,ligand PF3 is a ligand similar to CO,the energy difference between the reactant and product is small.

Tremor Suppression Method via Magnetorheological Damper and Fuzzy Neural Network Control

Based on the performance of magnetorheological damper we have developed,a tremor suppression method using human limb nonrigid characteristic was presented.The tremor suppression machine was designed,and the measure part and the tremor suppression part were separated.Subsequently,the mathematic models of fuzzy neural network and elbow nonrigid tremor were worked out.Using selected training data set,the off-line fuzzy neural network training was finished.Then the tremor suppression method was simulated in Matlab.From the simulation results,it is found that the tremor suppression method has presented suppresses tremor effectively,and the tremor amplitude and tremor suppression torque can be controlled with angle displacement sensor.

A diffusion-weighted imaging based diagnostic system for early detection of prostate cancer

A new framework for early diagnosis of prostate cancer using Diffusion-Weighted Imaging (DWI) is proposed. The proposed diagnostic approach consists of the following four steps to detect locations that are suspicious for prostate cancer: 1) In the first step, we isolate the prostate from the surrounding anatomical structures based on a Maximum A Posteriori (MAP) estimate of a new log-likelihood function that accounts for the shape priori, the spatial interaction, and the current appearance of prostate tissues and its background (surrounding anatomical structures);2) In order to take into account any local deformation between the segmented prostates at different b-values that could occur during the scanning process due to local motion, a non-rigid registration algorithm is employed;3) A KNN-based classifier is used to classify the prostate into benign or malignant based on three appearance features extracted from registered images;and 4) The tumor boundaries are determined using a level set deformable model controlled by the diffusion information and the spatial interactions between the prostate voxels. Preliminary experiments on 28 patients (17 malignant and 11 benign) resulted in 100% correct classification, showing that the proposed method is a promising supplement to current technologies (biopsy-based diagnostic systems) for the early diagnosis of prostate cancer.

Approach to Nonrigid Body Metamorphosis Using Generalized Morph-translation

An approach of morphing by decomposing two objects into sets of individual convex sub objects respectively and contructing the mapping between two sets is presented The Minkvski addition of two convex sub-objects according to their mapping ralationship is calculated, then all the Minkovski additions are combined to obtain the final result. Nonrigid body motion can be divided into nonrigid body metamorphosis and rigid body rotation A novel method for describing nonrigid body motion based on generalized morph-translation is proposed. This method can solve the metamorphosis problem of two non-homotopic objects. Experiments show tha this method can generate natural, high quality metamorphosis results with simple computation. This method can also be used in interpolation between two keyframes in 2D and 3D computer animation automatically.

A TV-l_1 Based Nonrigid Image Registration by Coupling Parametric and Non-parametric Transformation

To overcome the conflict between the global robustness and the local accuracy in the dense nonrigid image registration,we propose a union registration approach using a l1-norm based term to couple the parametric transformation and the non-parametric transformation. On one hand, we take the parametric deformation field as a constraint for the non-parametric registration, which is a strong constraint that guarantees the robustness of the non-parametric registration result. On the other hand, the non-parametric deformation field is taken as a force to improve the accuracy of the parametric registration. Then, an alternating optimization scheme is carried out to improve the accuracy of both the parametric registration and the non-parametric registration. Moreover, accounting for the effect of spatially-varying intensity distortions and the sparse gradient prior of the deformation field, we adopt the residual complexity(RC) as the similarity metric and the total variation(TV) as the regularization. Because of the TV-l1-l2 composite property of the objective function in our union image registration, we resort to the split Bregman iteration for the complex problem solving. Experiments with both synthetic and real images in different domains illustrate that this approach outperforms the separately performed parametric registration or non-parametric registration.