Segmenting whole heart from cardiac computed tomography(CT images can provide an important basis for the evaluation of cardiac function and help improve the accuracy of clinical diagnosis. Manual segmentation is the m...Segmenting whole heart from cardiac computed tomography(CT images can provide an important basis for the evaluation of cardiac function and help improve the accuracy of clinical diagnosis. Manual segmentation is the most accurate method for cardiac segmentation. But it is time consuming and not sufficiently reproducible. However, clinicians still rely on this method in practical applications. So a fully automatic method is needed to improve the segmentation efficiency. This pape proposes a registration-based automatic approach for three-dimensional(3D segmentation of cardiac CT images. The proposed method utilizes the similarity o cardiac CT images between different individuals, and uses registration to achieve the segmentation. Affine transformation is firstly implemented to achieve global coarse registration. Then, cubic B-splines are used to refine the local details in locally accurate registration. Mutual information(Ml) is used as the similarity measure, and adaptive stochastic gradient descent(ASGD) as the optimization algorithm. Ou method is applied to the dual-source cardiac CT images to segment whole heart Experimental results show that the proposed method can automatically segment whole heart from cardiac CT images.展开更多
With the growing deployment of unmanned aerial vehicles(UAVs)swarms in national defense,military operations,and emergency response,secure and reliable intra-swarm identity authentication has become critical for ensuri...With the growing deployment of unmanned aerial vehicles(UAVs)swarms in national defense,military operations,and emergency response,secure and reliable intra-swarm identity authentication has become critical for ensuring coordinated action and mission reliability.To address the drawbacks of public key infrastructure(PKI)based authentication in UAV swarms,namely,complex certificate management,strong dependence on centralized authorities,and authentication latency.We propose a certificateless identity authentication scheme for UAV swarms built on blockchain sharding.The scheme leverages sharding to execute authentication in parallel across multiple shards,significantly improving efficiency.Each UAV locally generates its public/private key pair and then adopts a registration-based encryption(RBE)mechanism:A registration algorithm binds the device identity to its key on the blockchain,ensuring public verifiability and immutability of identity mapping.On this basis,an authentication algorithm runs in which the initiator produces an authentication signature using a common reference string(CRS),on-chain public-key registration information,and its local private key,and the verifier rapidly validates the authentication message using the on-chain registration data and the identity of the initiator.The experimental results demonstrate that the proposed scheme achieves low-latency and high-throughput identity authentication in large-scale UAV swarm environments,providing a solid technical foundation and broad application prospects for trustworthy UAV swarm identity authentication.展开更多
基金National Natural Science Foundation of Chinagrant number:81101130+1 种基金the Fundamental Research Funds for the Central Universitygrant number:2012ZZ0095
文摘Segmenting whole heart from cardiac computed tomography(CT images can provide an important basis for the evaluation of cardiac function and help improve the accuracy of clinical diagnosis. Manual segmentation is the most accurate method for cardiac segmentation. But it is time consuming and not sufficiently reproducible. However, clinicians still rely on this method in practical applications. So a fully automatic method is needed to improve the segmentation efficiency. This pape proposes a registration-based automatic approach for three-dimensional(3D segmentation of cardiac CT images. The proposed method utilizes the similarity o cardiac CT images between different individuals, and uses registration to achieve the segmentation. Affine transformation is firstly implemented to achieve global coarse registration. Then, cubic B-splines are used to refine the local details in locally accurate registration. Mutual information(Ml) is used as the similarity measure, and adaptive stochastic gradient descent(ASGD) as the optimization algorithm. Ou method is applied to the dual-source cardiac CT images to segment whole heart Experimental results show that the proposed method can automatically segment whole heart from cardiac CT images.
基金supported by the National Natural Science Foundation of China under Grant No.62472075the Innovation Theory and Technology Group Fund of the Southwest China Institute of Electronic Technology under Grant No.2024jsq0207.
文摘With the growing deployment of unmanned aerial vehicles(UAVs)swarms in national defense,military operations,and emergency response,secure and reliable intra-swarm identity authentication has become critical for ensuring coordinated action and mission reliability.To address the drawbacks of public key infrastructure(PKI)based authentication in UAV swarms,namely,complex certificate management,strong dependence on centralized authorities,and authentication latency.We propose a certificateless identity authentication scheme for UAV swarms built on blockchain sharding.The scheme leverages sharding to execute authentication in parallel across multiple shards,significantly improving efficiency.Each UAV locally generates its public/private key pair and then adopts a registration-based encryption(RBE)mechanism:A registration algorithm binds the device identity to its key on the blockchain,ensuring public verifiability and immutability of identity mapping.On this basis,an authentication algorithm runs in which the initiator produces an authentication signature using a common reference string(CRS),on-chain public-key registration information,and its local private key,and the verifier rapidly validates the authentication message using the on-chain registration data and the identity of the initiator.The experimental results demonstrate that the proposed scheme achieves low-latency and high-throughput identity authentication in large-scale UAV swarm environments,providing a solid technical foundation and broad application prospects for trustworthy UAV swarm identity authentication.