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Artificial intelligence models based on non-contrast chest CT for measuring bone mineral density

中国医学影像技术 2024年第8期40卷 1231-1235页

作者： DUAN Wei YANG Guoqing LI Yang SHI Feng YANG Lian XIONG Xin CHEN Bei LI Yong FU Quanshui Department of Medical imaging North Sichuan Medical CollegeNanchong 637000China Department of Radiology Suining Central HospitalSuining 629000China Department of Radiology Suining Hospital of Traditional Chinese MedicineSuining 629000China shanghai united imaging intelligence co.ltd. Shanghai 201807China

Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶*** mean BMD of L1—L3 vertebrae were measured based on *** bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,*** operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of ***-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring *** Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of *** test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all Pconclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.

关键词： osteoporosis bone density tomography,X-ray computed artificial intelligence

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End-to-End Paired Ambisonic-Binaural Audio Rendering

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 502-513页

作者： Yin Zhu Qiuqiang Kong Junjie Shi Shilei Liu Xuzhou Ye Ju-Chiang Wang Hongming Shan Junping Zhang shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China Beijing ByteDance Technology co.ltd. Shanghai 201102China. Chinese University of Hong Kong Hong KongChina IEEE Institute of Science and Technology for Brain-Inspired intelligence and MOE Frontiers Center for Brain Science Fudan UniversityShanghai 200433 shanghai Center for Brain Science and Brain-Inspired Technology Shanghai 200031China

Binaural rendering is of great interest to virtual reality and immersive media. Although humans can naturally use their two ears to perceive the spatial information contained in sounds, it is a challenging task for machines to achieve binaural rendering since the description of a sound field often requires multiple channels and even the metadata of the sound sources. In addition, the perceived sound varies from person to person even in the same sound field. Previous methods generally rely on individual-dependent head-related transferred function(HRTF)datasets and optimization algorithms that act on HRTFs. In practical applications, there are two major drawbacks to existing methods. The first is a high personalization cost, as traditional methods achieve personalized needs by measuring HRTFs. The second is insufficient accuracy because the optimization goal of traditional methods is to retain another part of information that is more important in perception at the cost of discarding a part of the information. Therefore, it is desirable to develop novel techniques to achieve personalization and accuracy at a low cost. To this end, we focus on the binaural rendering of ambisonic and propose 1) channel-shared encoder and channel-compared attention integrated into neural networks and 2) a loss function quantifying interaural level differences to deal with spatial information. To verify the proposed method, we collect and release the first paired ambisonic-binaural dataset and introduce three metrics to evaluate the content information and spatial information accuracy of the end-to-end methods. Extensive experimental results on the collected dataset demonstrate the superior performance of the proposed method and the shortcomings of previous methods.

关键词： Ambisonic attention binaural rendering neural network

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Optics-driven drone

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Science China(Information Sciences) 2024年第2期67卷 322-324页

作者： Xuelong LI Guan HUANG Zhigang WANG Bin ZHAO School of Artificial intelligence OPtics and Electro Nics (iOPEN)Northwestern Polytechnical University shanghai Artificial intelligence Laboratory

In the field of vicinagearth security, low-altitude flying vehicles such as drones play an indispensable role in aerial remote sensing, intelligent search and rescue, etc. [1]. It can be foreseen that the autonomous and intelligent execution of complex tasks by drones is an inevitable trend for future development.

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Sequential Propagation of Chaos for Mean-Field BSDE Systems

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Chinese Annals of Mathematics,Series B 2024年第1期45卷 11-40页

作者： Xiaochen LI Kai DU shanghai Center for Mathematical Sciences Fudan UniversityShanghai 200433China. shanghai Artificial intelligence Laboratory 701 Yunjin RoadShanghai 200433China

A new class of backward particle systems with sequential interaction is proposed to approximate the mean-field backward stochastic differential *** is proven that the weighted empirical measure of this particle system converges to the law of the McKean-Vlasov system as the number of particles *** on the Wasserstein met-ric,quantitative propagation of chaos results are obtained for both linear and quadratic growth ***,numerical experiments are conducted to validate our theoretical results.

关键词： Backward propagation of chaos Particle system Sequential interaction McKean-Vlasov BSDE convergence rate

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Ultrahigh performance passive radiative cooling by hybrid polar dielectric metasurface thermal emitters

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Opto-Electronic Advances 2024年第4期7卷 17-25页

作者： Yinan Zhang Yinggang Chen Tong Wang Qian Zhu Min Gu Institute of Photonic Chips University of Shanghai for Science and TechnologyShanghai 200093China Centre for Artificial-intelligence Nanophotonics School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China

Real-world passive radiative cooling requires highly emissive,selective,and omnidirectional thermal emitters to maintain the radiative cooler at a certain temperature below the ambient temperature while maximizing the net cooling *** various selective thermal emitters have been demonstrated,it is still challenging to achieve these conditions sim-ultaneously because of the extreme difficulty in controlling thermal emission of photonic structures in *** we demonstrated hybrid polar dielectric metasurface thermal emitters with machine learning inverse design,en-abling a high emissivity of~0.92 within the atmospheric transparency window 8-13μm,a large spectral selectivity of~1.8 and a wide emission angle up to 80 degrees,*** selective and omnidirectional thermal emitter has led to a new record of temperature reduction as large as~15.4°C under strong solar irradiation of~800 W/m2,signific-antly surpassing the state-of-the-art *** designed structures also show great potential in tackling the urban heat island effect,with modelling results suggesting a large energy saving and deployment area *** research will make significant impact on passive radiative cooling,thermal energy photonics and tackling global climate change.

关键词： radiative cooling dielectric metasurfaces machine learning thermal emitters

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Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding

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Light(Science & Applications) 2024年第3期13卷 466-477页

作者： Xinyuan Fang Xiaonan Hu Baoli Li Hang Su Ke Cheng Haitao Luan Min Gu Institute of Photonic Chips University of Shanghai for Science and TechnologyShanghai 200093China Centre for Artificial-intelligence Nanophotonics School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China

Machine learning with optical neural networks has featured unique advantages of the information processing including high speed,ultrawide bandwidths and low energy consumption because the optical dimensions(time,space,wavelength,and polarization)could be utilized to increase the degree of ***,due to the lack of the capability to extract the information features in the orbital angular momentum(OAM)domain,the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network ***,we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network(CNN)based on Laguerre-Gaussian(LG)beam modes with diverse diffraction *** proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction,and deep-learning diffractive layers as a *** resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding,leading to an accuracy as high as 97.2%for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes,as well as a resistance to eavesdropping in point-to-point free-space ***,through extending the target encoded modes into multiplexed OAM states,we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%.Our work provides a deep insight to the mechanism of machine learning with spatial modes basis,which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

关键词： polarization mode momentum

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Distributed algorithm for solving variational inequalities over time-varying unbalanced digraphs

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control Theory and Technology 2024年第3期22卷 431-441页

作者： Yichen Zhang Yutao Tang Zhipeng Tu Yiguang Hong School of Artificial intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China Network Technology Laboratory Huawei Technologies Co.Ltd.Beijing 100095China Department of control Science and Engineering Tongji UniversityShanghai 200092China shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 200092China

In this paper,we study a distributed model to cooperatively compute variational inequalities over time-varying directed ***,each agent has access to a part of the full mapping and holds a local view of the global set *** virtue of an auxiliary vector to compensate the graph imbalance,we propose a consensus-based distributed projection algorithm relying on local computation and communication at each *** show the convergence of this algorithm over uniformly jointly strongly connected unbalanced digraphs with nonidentical local *** also provide a numerical example to illustrate the effectiveness of our algorithm.

关键词： Variational inequality Distributed computation Multi-agent system Weight-unbalanced graph

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Through-polymer,via technology-enabled,flexible,lightweight,and integrated devices for implantable neural probes

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Microsystems & Nanoengineering 2024年第2期10卷 279-291页

作者： Cunkai Zhou Ye Tian Gen Li Yifei Ye Lusha Gao Jiazhi Li Ziwei Liu Haoyang Su Yunxiao Lu Meng Li Zhitao Zhou Xiaoling Wei Lunming Qin Tiger H.Tao Liuyang Sun college of Electronics and Information Engineering Shanghai University of Electric PowerShanghaiChina 2020 X-Lab Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaiChina School of Graduate Study University of Chinese Academy of SciencesBeijingChina State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaiChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijingChina School of Physical Science and Technology ShanghaiTech UniversityShanghaiChina Center for Excellence in Brain Science and intelligence Technology Chinese Academy of SciencesShanghaiChina Neuroxess co. Ltd.(Jiangxi)NanchangJiangxiChina Guangdong Institute of intelligence Science and Technology HengqinZhuhaiGuangdongChina Tianqiao and Chrissy Chen Institute for Translational Research ShanghaiChina

In implantable electrophysiological recording systems,the headstage typically comprises neural probes that interface with brain tissue and integrated circuit chips for signal *** advancements in MEMS and CMOS technology have significantly improved these components,their interconnection still relies on conventional printed circuit boards and sophisticated *** conventional approach adds considerable weight and volume to the package,especially for high channel count *** address this issue,we developed a through-polymer via(TPV)method inspired by the through-silicon via(TSV)technique in advanced three-dimensional *** innovation enables the vertical integration of flexible probes,amplifier chips,and PCBs,realizing a flexible,lightweight,and integrated device(FLID).The total weight of the FLIDis only 25%that of its conventional counterparts relying on adapters,which significantly increased the activity levels of animals wearing the FLIDs to nearly match the levels of control animals without ***,by incorporating a platinum-iridium alloy as the top layer material for electrical contact,the FLID realizes exceptional electrical performance,enabling in vivo measurements of both local field potentials and individual neuron action *** findings showcase the potential of FLIDs in scaling up implantable neural recording systems and mark a significant advancement in the field of neurotechnology.

关键词： alloy neural recording

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Improving fault localization with pre-training

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Frontiers of computer Science 2024年第1期18卷 247-249页

作者： Zhuo ZHANG Ya LI Jianxin XUE Xiaoguang MAO School of Information Technology and Engineering Guangzhou College of CommerceGuangzhou 511363China Ningbo Artificial intelligence Institute Shanghai Jiao Tong UniversityNingbo 315000China Institute for Artificial intelligence Shanghai Polytechnic UniversityShanghai 210209China college of computer National University of Defense TechnologyChangsha 410073China

1 Introduction For developers,fault localization is the most tedious and time-consuming *** order to reduce the burden of developers,researchers have developed various techniques to help reduce the cost of locating faults based on possibility of containing a fault in program statements[1].Among them,coverage-based fault localization is one of the most studied automated fault localization ***-based fault localization methods utilize a type of preliminary information to localize the faults in programs,which is a matrix of statements’coverage *** value of each element is 1 or 0,in which 1 means a statement is executed and 0 denotes a statement is not executed[1].

关键词： fault statement utilize

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A novel lightweight computerized ECG interpretation approach based on clinical 12-lead data

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Science China(Technological Sciences) 2024年第2期67卷 449-463页

作者： LIU YunQing QIN ChengJin LIU JinLei JIN YanRui LI ZhiYuan ZHAO LiQun LIU ChengLiang School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Key Labof Artificial intelligence(Ministryof Education) AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Cardiology Shanghai First Peoples Hospital Affiliated to Shanghai Jiao Tong UniversityShanghai 200080China

Although 12-lead electrocardiograms(ECGs)provide a wide range of spatiotemporal characteristics,interpreting them for arrhythmia detection is difficult due to a lack of reliable large-scale clinical ***,we proposed an innovative lightweight computerized ECG interpretation approach based on 12-lead *** model was trained,validated,and tested on 53845 standard 12-lead ECG records collected at shanghai First People’s Hospital in affiliation with shanghai Jiao Tong *** experiments revealed that our approach had a classification accuracy of 94.41%in the classification task of seven types of rhythms,which was markedly superior to related single-lead and 12-lead ECG classification ***,the average receiver operating characteristic area under the curve reached a value of 0.940,and the precision values for sinus tachycardia and sinus bradycardia were 0.945 and 0.91,respectively,with specificity values of 0.996 and *** employing our boosting method,we were able to improve the accuracy to 94.85%.To investigate the performance degradation of the proposed neural network in some classes,an ECG cardiologist was enlisted to review questionable ECGs;this process provides a promising direction for network performance ***,the proposed computerized ECG interpretation approach has practical significance because it could help professional physicians analyze patients’heart conditions based on real-time 12-lead ECG or grade their disease severity in advance.

关键词： computerized ECG interpretation large-scale 12-lead clinical ECG database lightweight neural network

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