Multi‐modal brain image registration has been widely applied to functional localisation,neurosurgery and computational anatomy.The existing registration methods based on the dense deformation fields involve too many ...Multi‐modal brain image registration has been widely applied to functional localisation,neurosurgery and computational anatomy.The existing registration methods based on the dense deformation fields involve too many parameters,which is not conducive to the exploration of correct spatial correspondence between the float and reference images.Meanwhile,the unidirectional registration may involve the deformation folding,which will result in the change of topology during registration.To address these issues,this work has presented an unsupervised image registration method using the free form deformation(FFD)and the symmetry constraint‐based generative adversarial networks(FSGAN).The FSGAN utilises the principle component analysis network‐based structural representations of the reference and float images as the inputs and uses the generator to learn the FFD model parameters,thereby producing two deformation fields.Meanwhile,the FSGAN uses two discriminators to decide whether the bilateral registration have been realised simultaneously.Besides,the symmetry constraint is utilised to construct the loss function,thereby avoiding the deformation folding.Experiments on BrainWeb,high grade gliomas,IXI and LPBA40 show that compared with state‐of‐the‐art methods,the FSGAN provides superior performance in terms of visual comparisons and such quantitative indexes as dice value,target registration error and computational efficiency.展开更多
We implemented accurate FFD in terms of triangular Bezier surfaces as matrix multiplications in CUDA and rendered them via OpenGL. Experimental results show that the proposed algorithm is more efficient than the previ...We implemented accurate FFD in terms of triangular Bezier surfaces as matrix multiplications in CUDA and rendered them via OpenGL. Experimental results show that the proposed algorithm is more efficient than the previous GPU acceleration algorithm and tessel- lation shader algorithms.展开更多
This paper presents a skin deformation algorithm for creating 3D characters or virtual human models. The algorithm can be applied to rigid deformation, joint dependent localized deformation, skeleton driven deformatio...This paper presents a skin deformation algorithm for creating 3D characters or virtual human models. The algorithm can be applied to rigid deformation, joint dependent localized deformation, skeleton driven deformation, cross contour deformation, and free-form deformation (FFD). These deformations are computed and demonstrated with examples and the algorithm is applied to overcome the difficulties in mechanically simulating the motion of the human body by club-shape models. The techniques described in this article enables the reconstruction of dynamic human models that can be used in defining and representing the geometrical and kinematical characteristics of human motion.展开更多
We present a new method for image deformation. The warping technique provides smooth distortion with intuitive and easy manipulation. Driven by a restrained force field, the input image is deformed gradually and conti...We present a new method for image deformation. The warping technique provides smooth distortion with intuitive and easy manipulation. Driven by a restrained force field, the input image is deformed gradually and continuously. The method allows us to customize the force fields and the region of interest manually through some simple steps. Experimental results demonstrate the effectiveness and convenience of the approach.展开更多
飞翼布局因其独特的翼身融合的气动外形,大大提高了飞行器的有效升力面积,外形优化问题和布局优化对于此类构型气动性能的提升同样重要。本文为解决飞翼布局无人机气动外形优化问题,建立了高效的参数化建模方法,实现了适应复杂外形的几...飞翼布局因其独特的翼身融合的气动外形,大大提高了飞行器的有效升力面积,外形优化问题和布局优化对于此类构型气动性能的提升同样重要。本文为解决飞翼布局无人机气动外形优化问题,建立了高效的参数化建模方法,实现了适应复杂外形的几何参数化变形控制,将基于梯度的优化算法、离散伴随方法与基于RANS(Reynolds average Navier-Stokes)方程的计算流体力学(Computational fluid dynamics,CFD)方法相结合,对飞翼布局无人机完成了气动外形的优化减阻设计,升阻比提升了7.17%。优化结果表明,在满足约束要求的前提下,基于上述技术的气动优化设计方法对翼身融合类构型具有良好的适应性,能有效改善无人机的气动性能。展开更多
Titanium hollow blades are characterized with lightweight and high structural strength, which are widely used in advanced aircraft engines nowadays. Superplastic forming/diffusion bonding (SPF/DB) combined with nume...Titanium hollow blades are characterized with lightweight and high structural strength, which are widely used in advanced aircraft engines nowadays. Superplastic forming/diffusion bonding (SPF/DB) combined with numerical control (NC) milling is a major solution for manufacturing titanium hollow blades. Due to the shape deviation caused by multiple heat and pressure cycles in the SPF/DB process, it is hard to manufacture the leading and tailing edges by the milling process. This paper presents a new adaptive machining approach using free-form deformation to solve this problem. The actual SPF/DB shape of a hollow blade was firstly inspected by an on-machine measurement method. The measured point data were matched to the nominal SPF/DB shape with an improved ICP algorithm afterwards, by which the point-pairs between the measurement points and their corresponding points on the nominal SPF/DB shape were established, and the maximum modification amount of the final nominal shape was constrained. Based on the displacements between the point-pairs, an accurate FFD volume was iteratively calculated. By embedding the final nominal shape in the deformation space, a new final shape of the hollow blade was built. Finally, a series of measurement and machining tests was performed, the results of which validated the feasibility of the proposed adaptive machining approach.展开更多
In this paper, we propose a novel free-form deformation (FFD) technique, RDMS-FFD (Rational DMS-FFD), based on rational DMS-spline volumes. RDMS-FFD inherits some good properties of rational DMS-spline volumes and...In this paper, we propose a novel free-form deformation (FFD) technique, RDMS-FFD (Rational DMS-FFD), based on rational DMS-spline volumes. RDMS-FFD inherits some good properties of rational DMS-spline volumes and combines more deformation techniques than previous FFD methods in a consistent framework, such as local deformation, control lattice of arbitrary topology, smooth deformation, multiresolution deformation and direct manipulation of deformation. We first introduce the rational DMS-spline volume by directly generalizing the previous results related to DMS-splines. How to generate a tetrahedral domain that approximates the shape of the object to be deformed is also introduced in this paper. Unlike the traditional FFD techniques, we manipulate the vertices of the tetrahedral domain to achieve deformation results. Our system demonstrates that RDMS-FFD is powerful and intuitive in geometric modeling.展开更多
基金supported in part by the National Key Research and Development Program of China under Grant 2018Y FE0206900in part by the National Natural Science Foundation of China under Grant 61871440in part by the CAAIHuawei MindSpore Open Fund.We gratefully acknowledge the support of MindSpore for this research.
文摘Multi‐modal brain image registration has been widely applied to functional localisation,neurosurgery and computational anatomy.The existing registration methods based on the dense deformation fields involve too many parameters,which is not conducive to the exploration of correct spatial correspondence between the float and reference images.Meanwhile,the unidirectional registration may involve the deformation folding,which will result in the change of topology during registration.To address these issues,this work has presented an unsupervised image registration method using the free form deformation(FFD)and the symmetry constraint‐based generative adversarial networks(FSGAN).The FSGAN utilises the principle component analysis network‐based structural representations of the reference and float images as the inputs and uses the generator to learn the FFD model parameters,thereby producing two deformation fields.Meanwhile,the FSGAN uses two discriminators to decide whether the bilateral registration have been realised simultaneously.Besides,the symmetry constraint is utilised to construct the loss function,thereby avoiding the deformation folding.Experiments on BrainWeb,high grade gliomas,IXI and LPBA40 show that compared with state‐of‐the‐art methods,the FSGAN provides superior performance in terms of visual comparisons and such quantitative indexes as dice value,target registration error and computational efficiency.
基金Supported by the National Natural Science Foundation of China(61170138 and 61472349)
文摘We implemented accurate FFD in terms of triangular Bezier surfaces as matrix multiplications in CUDA and rendered them via OpenGL. Experimental results show that the proposed algorithm is more efficient than the previous GPU acceleration algorithm and tessel- lation shader algorithms.
基金supported by Shanghai Science and Technology Committee (No. 08515810200)Jiangsu Province Development Foundation (No. BS2007048)
文摘This paper presents a skin deformation algorithm for creating 3D characters or virtual human models. The algorithm can be applied to rigid deformation, joint dependent localized deformation, skeleton driven deformation, cross contour deformation, and free-form deformation (FFD). These deformations are computed and demonstrated with examples and the algorithm is applied to overcome the difficulties in mechanically simulating the motion of the human body by club-shape models. The techniques described in this article enables the reconstruction of dynamic human models that can be used in defining and representing the geometrical and kinematical characteristics of human motion.
文摘We present a new method for image deformation. The warping technique provides smooth distortion with intuitive and easy manipulation. Driven by a restrained force field, the input image is deformed gradually and continuously. The method allows us to customize the force fields and the region of interest manually through some simple steps. Experimental results demonstrate the effectiveness and convenience of the approach.
基金supported in part by the National Natural Science Foundation of China(No.11972180)。
文摘飞翼布局因其独特的翼身融合的气动外形,大大提高了飞行器的有效升力面积,外形优化问题和布局优化对于此类构型气动性能的提升同样重要。本文为解决飞翼布局无人机气动外形优化问题,建立了高效的参数化建模方法,实现了适应复杂外形的几何参数化变形控制,将基于梯度的优化算法、离散伴随方法与基于RANS(Reynolds average Navier-Stokes)方程的计算流体力学(Computational fluid dynamics,CFD)方法相结合,对飞翼布局无人机完成了气动外形的优化减阻设计,升阻比提升了7.17%。优化结果表明,在满足约束要求的前提下,基于上述技术的气动优化设计方法对翼身融合类构型具有良好的适应性,能有效改善无人机的气动性能。
基金the financial supports of the National Natural Science Foundation of China(No.51475233)the Fundamental Research Funds for Central Universities(No.NZ2016107)the Jiangsu Innovation Program for Graduate Education(No.CXLX13_139)
文摘Titanium hollow blades are characterized with lightweight and high structural strength, which are widely used in advanced aircraft engines nowadays. Superplastic forming/diffusion bonding (SPF/DB) combined with numerical control (NC) milling is a major solution for manufacturing titanium hollow blades. Due to the shape deviation caused by multiple heat and pressure cycles in the SPF/DB process, it is hard to manufacture the leading and tailing edges by the milling process. This paper presents a new adaptive machining approach using free-form deformation to solve this problem. The actual SPF/DB shape of a hollow blade was firstly inspected by an on-machine measurement method. The measured point data were matched to the nominal SPF/DB shape with an improved ICP algorithm afterwards, by which the point-pairs between the measurement points and their corresponding points on the nominal SPF/DB shape were established, and the maximum modification amount of the final nominal shape was constrained. Based on the displacements between the point-pairs, an accurate FFD volume was iteratively calculated. By embedding the final nominal shape in the deformation space, a new final shape of the hollow blade was built. Finally, a series of measurement and machining tests was performed, the results of which validated the feasibility of the proposed adaptive machining approach.
基金supported by the National Natural Science Foundation of China under Grant Nos. 60773179 and 60473130the National Basic Research 973 Program of China under Grant No. 2004CB318000
文摘In this paper, we propose a novel free-form deformation (FFD) technique, RDMS-FFD (Rational DMS-FFD), based on rational DMS-spline volumes. RDMS-FFD inherits some good properties of rational DMS-spline volumes and combines more deformation techniques than previous FFD methods in a consistent framework, such as local deformation, control lattice of arbitrary topology, smooth deformation, multiresolution deformation and direct manipulation of deformation. We first introduce the rational DMS-spline volume by directly generalizing the previous results related to DMS-splines. How to generate a tetrahedral domain that approximates the shape of the object to be deformed is also introduced in this paper. Unlike the traditional FFD techniques, we manipulate the vertices of the tetrahedral domain to achieve deformation results. Our system demonstrates that RDMS-FFD is powerful and intuitive in geometric modeling.