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A 12-bit multichannel ADC for pixel detectors in particle physics and nuclear imaging

Science China(Technological Sciences) 2010年第5期53卷 1208-1214页

作者： WEI Wei1,2,3.WANG Zheng1,3.& ZHAO JingWei1,3.1 Institute of High Energy Physics,chinese academy of Sciences,beijing 10004.,China 2 Graduate University of chinese academy of Sciences,beijing 10004.,China 3.key lab of nuclear detection technology and nuclear electronics of chinese academy of Sciences,beijing 10004.,China 1. Institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China2. Graduate University of Chinese Academy of Sciences Beijing 100049 China3. Key Lab of Nuclear Detection Technology and Nuclear Electronics of Chinese Academy of Sciences Beijing 100049 China

Modern pixel detectors in nuclear and particle physics experiments and also in nuclear imaging,starve for highly integrated application specified integrated circuit(ASIC),whereas in China the study of ASIC still stays far away from practical *** lack of ASIC strictly limits the research and development of domestic high energy physics field.A 12-bit multichannel ADC designed for high density readout is introduced as a major candidate for solution.A precise model is discussed and the simulation fully agrees with the model,which indicates a key principle of *** is performed according to the given rule,and novel layout techniques are carried *** results in all aspects are also obtained,showing an excellent real performance,which satisfies the practical requirement.

关键词： application specified integrated circuit high density readout Wilkinson ADC multi-channel ADC

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一种新的高效MMSE-SIC检测算法

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系统仿真学报 2011年第7期23卷 1350-1353页

作者：包亚伟赵慧蒋华王文博吴斌泛网无线通信教育部重点实验室北京邮电大学北京100876 北京电子科技学院北京100070 中国科学院微电子研究所北京100029

传统的V-BLAST系统检测算法,由于存在矩阵求逆的操作,其计算复杂度与发射天线数的立方成正比,在发射天线较多时,对接收机信号处理能力要求较高。于是提出了一种具有更低复杂度的排序串行干扰消除算法。该算法利用施密特正交化分解方法,... 详细信息

传统的V-BLAST系统检测算法,由于存在矩阵求逆的操作,其计算复杂度与发射天线数的立方成正比,在发射天线较多时,对接收机信号处理能力要求较高。于是提出了一种具有更低复杂度的排序串行干扰消除算法。该算法利用施密特正交化分解方法,有效地避免了循环矩阵求逆运算,在不降低误比特率性能的情况下,使得检测算法大为简化,其计算复杂度与发射天线数的平方成正比。同时,该算法使排序和检测过程相互独立出来,提高了算法应用的灵活性。

关键词：垂直-贝尔实验室分层空时结构最小均方误差检测排序施密特正交化

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The study on stability and reliability of the nuclear detector

The study on stability and reliability of the nuclear detect...

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Measurement Touch the World——IEEE 2011 10th International Conference on Electronic Measurement & Instruments(ICEMI’2011)

作者： Wu Yini Wu Jianping Luo Yaoyao Wu Haibiao Cheng Guodong College of nuclear technology and Automatic Engineering Chengdu University of technology Provincial {3. {4. of Applied nuclear Techniques in Geosciences Chengdu 610059 Sichuan China

Because of measurement environment and its own performance defect,the poor stability of nuclear radiation detector used on portable nuclear instrument leads to spectrum drift and decrease of energy resolution,which causes reduction of the detect *** results in lower measurement precision and accuracy of the ***,the stabilization method based on hardware and software was *** is difficult to solve the problem about Spectrum drift caused by multiple *** slove the nonlinear problems caused by interference source,Multi-sensor Data Fusion Technique is adopt to design the intelligent nuclear detector with the Self-compensation *** shows that the results of the project can improve the stability and reliability of the fieldwork measurement in system of the nuclear *** that it will improve the adaptive ability of the nuclear instruments to measuring environment.

关键词： nuclear detector Spectrum drift Stability Multi-sensory information fusion

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用于中国散裂中子源多功能反射谱仪的高气压多丝正比室探测器的研制

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物理学报 2018年第7期67卷 108-116页

作者：温志文祁辉荣张余炼王海云刘凌王艳凤张建李玉红孙志嘉兰州大学核科学与技术学院兰州730000 核探测与核电子学国家重点实验室北京100049 中国科学院高能物理研究所北京100049 中国科学院大学北京100049

中国散裂中子源需要建设一台多功能反射谱仪中子探测器,满足在10年运行期间内,50%(@2A)以上的探测效率、好于2 mm的二维位置分辨、200 mm×200 mm的灵敏面积、3.的n/γ分辨能力及良好的二维成像性能.基于此要求,探测器因此采用基于高气... 详细信息

中国散裂中子源需要建设一台多功能反射谱仪中子探测器,满足在10年运行期间内,50%(@2A)以上的探测效率、好于2 mm的二维位置分辨、200 mm×200 mm的灵敏面积、3.的n/γ分辨能力及良好的二维成像性能.基于此要求,探测器因此采用基于高气压~3.e气体的多丝正比室,并以满足反射谱仪的探测效率、位置分辨、长期稳定工作和n/y分辨能力为目标进行探测器的设计.本文经过模拟和实验计算得出:以9 mm厚的铝合金入射窗、铝丝密封的高气压腔体和6 bar^3.e+2.5 bar C_3._8的工作气体的设计,可满足探测器对2 A中子10年运行期间内54.以上的探测效率要求;探测器对中子的位置分辨可达到1.4.mm左右;设计的气体净化系统,拥有2 L/min的气流速度可有效去除探测器内的负电性杂质气体,气体循环净化后可提高探测器约27%的气体增益,保证探测器长期稳定的运行;通过对^(252)Cf中子源的能谱测量和成像测量,得出探测器的n/γ分辨能力在5倍以上和均匀的成像结果.研制的探测器满足反射谱仪需求,并已在中国散裂中子源反射谱仪靶站就位联调.

关键词：多丝正比室探测器效率位置分辨 n/γ分辨

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Radar Weak Target detection and Location Based on Hough Transform

Radar Weak Target Detection and Location Based on Hough Tran...

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2002年第6届信号处理国际会议

作者： Du Pengfei Wang Yongliang Sun Wenfeng School of Electronic Science and Engineering National University of Defence technology Changsha Hunan 4.0073.China key Research {3. Wuhan Radar academy Wuhan Hubei 4.0010 China

＜正＞ The Hough transform （HT） is analyzed and applied to radar weak target detection and location in this paper. The literature [1], in which only search radar is used, is extended to more general radar system. The theoretical analysis and experimental results used real-life radar data show that the presented method performs well in the strong clutter background, and robust to the clutter distribution.

关键词： Hough transform (HT) Weak target detection and location

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A MULTIUSER DETECTOR BASED ON BLIND SIGNAL SEPARATION

A MULTIUSER DETECTOR BASED ON BLIND SIGNAL SEPARATION

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2003.International Conference on Communication technology

作者： Jianfeng CHEN Xiaolong ZHU Xianda ZHANG key lab for Radar Signal Processing Xidian University Xi’an 710071 China Department of Automation Tsinghua University beijing 10008{3.China

Conventional RAKE receiver dis- tinguishes each user by crosscorrelation of the spread sequences and achieves detection of the desired user. In practical applications, however, the performance of rece

关键词： multi-user detection blind sig- nal separation DS-CDMA

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Study design of deep learning based automatic detection of cerebrovascular diseases on medical imaging: a position paper from chinese Association of Radiologists

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Intelligent Medicine 2022年第4期2卷 221-229页

作者： Longjiang Zhang Zhao Shi Min Chen Yingmin Chen Jingliang Cheng Li Fan Nan Hong Wenxiao Jia Guihua Jiang Shenghong Ju Xiaogang Li Xiuli Li Changhong Liang Weihua Liao Shiyuan Liu Zaiming Lu Lin Ma Ke Ren Pengfei Rong Bin Song Gang Sun Rongpin Wang Zhibo Wen Haibo Xu Kai Xu Fuhua Yan Yizhou Yu Yunfei Zha Fandong Zhang Minwen Zheng Zhen Zhou Wenzhen Zhu Guangming Lu Zhengyu Jin on behalf of chinese Association of Radiologists Department of Radiology Affiliated Jinling HospitalMedical School of Nanjing UniversityNanjingJiangsu 210002China Department of Radiology Beijing HospitalNational Center of GerontologyBeijing 100005China Department of Radiology Hebei General HospitalShijiazhuangHebei 050199China Department of Magnetic Resonance Imaging The First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenan 450052China Department of Medical Imaging and nuclear Medicine Changzheng Hospital of Naval Medical UniversityShanghai 200072China Department of Radiology Peking University People’s HospitalBeijing 100044China Imaging Center First AffiliatedHospital of Xinjiang Medical UniversityUrumqiXinjiang Uygur Autonomous Region 830054China Department of Medical Imaging Guangdong Second Provincial General HospitalGuangzhouGuangdong 510050China Department of Radiology Zhongda HospitalSchool of MedicineSoutheast UniversityNanjingJiangsu 211189China Department of Radiology General Hospital of Northern Theater CommandShenyangLiaoning 110011China DeepWise AI lab.beijing 100089 China Department of Radiology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhouGuangdong 519041China Department of Radiology Xiangya HospitalCentral South UniversityChangshaHunan 410008China Department of Radiology Shengjing Hospital of China Medical UniversityShenyangLiaoning 110001China Department of Radiology Chinese PLA(People’s Liberation Army)General HospitalBeijing 100853China Department of Radiology Xiang’an Hospital of Xiamen UniversitySchool of MedicineXiamen UniversityXiamenFujian 361005China Department of Radiology Third Xiangya HospitalCentral South UniversityChangshaHunan 410013China Department of Radiology Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China HospitalSichuan UniversityChengduSichuan 610044China Department of nuclear Medicine 960 Hospital of PLAJi’nanShandong 250012China Department of Radiology Guizhou Provincial People’s Hosp

In recent years,with the development of artificial intelligence,especially deep learning technology,researches on automatic detection of cerebrovascular diseases on medical images have made tremendous progress and these models are gradually entering into clinical ***,because of the complexity and flexibility of the deep learning algorithms,these researches have great variability on model building,validation process,performance description and results *** lack of a reliable,consistent,standardized design protocol has,to a certain extent,affected the progress of clinical translation and technology development of computer aided detection *** reviewing a large number of literatures and extensive discussion with domestic experts,this position paper put forward recommendations of standardized design on the {4. steps of deep learning-based automatic image detection models for cerebrovascular *** further research and application expansion,this position paper would continue to be updated and gradually extended to evaluate the generalizability and clinical application efficacy of such tools.

关键词： Cerebrovascular diseases Deep learning Study design Medical imaging

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