Objective To evaluate the clinical applications and limitations of CT virtual endoscopy (CTVE) in theauditory ossicular chain.Methods CTVE of the auditory ossicular chain was performed with 1.0 mm collimation at pitc...Objective To evaluate the clinical applications and limitations of CT virtual endoscopy (CTVE) in theauditory ossicular chain.Methods CTVE of the auditory ossicular chain was performed with 1.0 mm collimation at pitch 1.0, bone algorithm, 9.6 cm field of view, and 0.1 - 0.2 mm reconstruction interval in 40 patients with middle ear diseases. 30 cases were confirmed by surgery. Results were compared with the findings of axial high resolution CT (HRCT) and multiplanar reformation (MPR) images and surgery.Results The accuracy of CTVE images in detecting ossicular destruction was 92.6%, significantly higher than that of axial HRCT (83.9%) and multiplanar reformation (76.5%) images. CTVE could also clearty reveal the postoperative condition and congenital dysplasia of the auditory ossicular chain.Conclusions CTVE can clearly demonstrate a three-dimensional image of the auditory ossicular chain and is useful in evaluating diseases of the ear, especially the auditory ossicles. CTVE could not clearly demonstrate abnormal soft tissue within the tympanic cavity, abnormal changes of the tympanic membrane and tympanic walls, and could be easily influenced by artificial factors.展开更多
The electromyography(EMG)signal is the biocurrent associated with muscle contraction and can be used as the input signal to a myoelectric intelligent bionic hand to control different gestures of the hand.Increasing th...The electromyography(EMG)signal is the biocurrent associated with muscle contraction and can be used as the input signal to a myoelectric intelligent bionic hand to control different gestures of the hand.Increasing the number of myoelectric-signal channels can yield richer information of motion intention and improve the accuracy of gesture recognition.However,as the number of acquisition channels increases,its effect on the improvement of the accuracy of gesture recognition gradually diminishes,resulting in the improvement of the control effect reaching a plateau.To address these problems,this paper presents a proposed method to improve gesture recognition accuracy by virtually increasing the number of EMG signal channels.This method is able to improve the recognition accuracy of various gestures by virtually increasing the number of EMG signal channels and enriching the motion intention information extracted from data collected from a certain number of physical channels,ultimately providing a solution to the issue of the recognition accuracy plateau caused by saturation of information from physical recordings.Meanwhile,based on the idea of the filtered feature selection method,a quantitative measure of sample sets(separability of feature vectors[SFV])derived from the divergence and correlation of the extracted features is introduced.The SFV value can predict the classification effect before performing the classification,and the effectiveness of the virtual-dimension increase strategy is verified from the perspective of feature set differentiability change.Compared to the statistical motion intention recognition success rate,SFVis a more representative and faster measure of classification effectiveness and is also suitable for small sample sets.展开更多
We study the pseudoholomorphic curves with brake symmetry in symplectization of a closed contact manifold.We introduce the pseudoholomorphic curves with brake symmetry and the corresponding moduli space.Then we get th...We study the pseudoholomorphic curves with brake symmetry in symplectization of a closed contact manifold.We introduce the pseudoholomorphic curves with brake symmetry and the corresponding moduli space.Then we get the virtual dimension of the moduli space.展开更多
文摘Objective To evaluate the clinical applications and limitations of CT virtual endoscopy (CTVE) in theauditory ossicular chain.Methods CTVE of the auditory ossicular chain was performed with 1.0 mm collimation at pitch 1.0, bone algorithm, 9.6 cm field of view, and 0.1 - 0.2 mm reconstruction interval in 40 patients with middle ear diseases. 30 cases were confirmed by surgery. Results were compared with the findings of axial high resolution CT (HRCT) and multiplanar reformation (MPR) images and surgery.Results The accuracy of CTVE images in detecting ossicular destruction was 92.6%, significantly higher than that of axial HRCT (83.9%) and multiplanar reformation (76.5%) images. CTVE could also clearty reveal the postoperative condition and congenital dysplasia of the auditory ossicular chain.Conclusions CTVE can clearly demonstrate a three-dimensional image of the auditory ossicular chain and is useful in evaluating diseases of the ear, especially the auditory ossicles. CTVE could not clearly demonstrate abnormal soft tissue within the tympanic cavity, abnormal changes of the tympanic membrane and tympanic walls, and could be easily influenced by artificial factors.
文摘The electromyography(EMG)signal is the biocurrent associated with muscle contraction and can be used as the input signal to a myoelectric intelligent bionic hand to control different gestures of the hand.Increasing the number of myoelectric-signal channels can yield richer information of motion intention and improve the accuracy of gesture recognition.However,as the number of acquisition channels increases,its effect on the improvement of the accuracy of gesture recognition gradually diminishes,resulting in the improvement of the control effect reaching a plateau.To address these problems,this paper presents a proposed method to improve gesture recognition accuracy by virtually increasing the number of EMG signal channels.This method is able to improve the recognition accuracy of various gestures by virtually increasing the number of EMG signal channels and enriching the motion intention information extracted from data collected from a certain number of physical channels,ultimately providing a solution to the issue of the recognition accuracy plateau caused by saturation of information from physical recordings.Meanwhile,based on the idea of the filtered feature selection method,a quantitative measure of sample sets(separability of feature vectors[SFV])derived from the divergence and correlation of the extracted features is introduced.The SFV value can predict the classification effect before performing the classification,and the effectiveness of the virtual-dimension increase strategy is verified from the perspective of feature set differentiability change.Compared to the statistical motion intention recognition success rate,SFVis a more representative and faster measure of classification effectiveness and is also suitable for small sample sets.
基金The first author was supported by the China Scholarship Council(CSC)(No.201806200130),the LPMC of Ministry of Education of China,and Nankai Zhide Foundation and Nankai UniversityThe second author was supported by the National Natural Science Foundation of China(Grant Nos.11971245,11771331),the LPMC of Ministry of Education of China,the Nankai Zhide Foundation and Nankai University.
文摘We study the pseudoholomorphic curves with brake symmetry in symplectization of a closed contact manifold.We introduce the pseudoholomorphic curves with brake symmetry and the corresponding moduli space.Then we get the virtual dimension of the moduli space.
