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Nicola D’Ascenzo

  • 王百宗
  • 2023-05-19
  • 1806

Nicola D’AscenzoProfessor, Doctoral Supervisor

Professor, Department of Electronic Engineering and Information Science, University of Science and Technology of China; Researcher, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center; Inventor of Agri-PET imaging;

Email: nicoladascenzo@ustc.edu.cn

Introduction

Prof. D’Ascenzo (1982, 41 y.o.) joined PETlab in early 2013 and was awarded with the National 1000 Young Talent program in 2016. His international research team focuses on the development of new digital imaging technologies for portable and shape-adaptable PET systems for more than 20 years.  He has been invited in 2022 to join USTC as Full Professor at the department of electronic engineering and information science.

To contrast adverse impact of climate-change-related stressors for sustainable agriculture, Prof. D’Ascenzo explores the frontier of PET setting the theoretical, methodological, and technological fundaments for the transition from a lab-based plant PET imaging to an in-field Agri-PET imaging. In-field measurements obtained with the new portable AGRI-PET system technology developed by Prof. D’Ascenzo, in fact, reflect the complexity of a natural environment, which lab-based experiments can only partially reproduce. The system is equipped with a Kinetically Consistent Data Assimilation (KCDA) signal processing approach for incomplete dynamic crop PET signals, which allows the quantitative interpretation of the PET spatiotemporal signals.

To study brain functionality in neurological diseases, Prof. D’Ascenzo explores the frontier of brain PET technology, investigating the potential of a digital Helmet PET system, which adapts to the head shape with a half-spherical configuration. Its high sensitivity and count-rate capability enable short dynamic frames, opening the possibility of high-resolution dynamic imaging of subjects in free-motion.

The compactness and portability of the digital AGRI-PET system is enabled also by a compact sensor technology, the CMOS SiPM, developed by Prof. D’Ascenzo. The sensor, realized in a CMOS compatible process, reaches an unprecedented photo detection efficiency of 43% at a 420 nm spectral region and a single photon time resolution of 70 ps (FWHM). On this basis, he is one of the inventors of the MVT-SiPM, which embeds single photon spatiotemporal digital signal processing on a single chip, enabling high resolution and sensitivity digital PET technologies.

The Agri-PET technology has been recognized internationally and is adopted at the Digital Imaging Multimodal Platform node of the Eurobioimaging European Research Infrastructure in Italy, and at the PETAL international consortium on dynamic crop functional imaging.   Prof. D’Ascenzo has published more than 200 top journals and conference papers and has filled 15 patents.  

Research interests

单光子探测芯片中光子响应机制与信号处理方法

新型PET系统设计与成像方法研究(头盔PETAgri-PET

Major Part-time job title

Scientific advisor of the Digital Imaging Multimodal Platform, EUROBIOIMAGING, Italy; Member of the international advisory committee of the INFIERI Summer School Series, Co-chair of the Sensors and Detectors section of the IEEE Photonics Society, Member of the Organizing Committee of the first workshop on PET electronics and technologies at the Fraunhofer German Institute

Research projects:

中德科学基金研究交流中心, 中德合作交流, M-0387, PET-CT研究, 2021-01 2023-12, 149.55万元, 在研, 参与

国家自然科学基金青年科学基金目,61604059,硅光倍增器的雪崩倍增程研究 2017-012019-1222万元,已结题,主持

国家自然科学基金青年科学基金项目,61501197,基于全数字化的闪烁脉冲时间标记2016-012018-1227.6万元,已结题,参与

国务院其他部委基金项目,20160950,全数字硅光电倍增器件研发,2016-012018-12, 200万元,已结题,主持

Talents development

He has been teaching for 10 years, and has carried out teaching work in electrical engineering, automation, medical physics, biomedical engineering and other majors, has supervised undergraduate and graduate students. International and cross-disciplinary team work is the basis of his approach to teaching, education and research. The team recruits several doctoral / master's students/undergraduates every year, and welcomes outstanding students from information and communication engineering, electronic science and technology, control science and engineering, computer science and technology, nuclear science and technology, physics (particle physics and nuclear physics, atomic and molecular physics), mathematics (probability theory and mathematical statistics, computational mathematics), biomedical engineering and other related majors to join. The team has overseas branches in Italy and Germany. Space is limited, so please contact us as soon as possible.

Representative papers


  1. Antonecchia E, D’Ascenzo N, Cantalamessa S,      et al. Development and evaluation of a prototype of shape-adaptable and      portable All-Digital PET system for in-lab and in-field plant imaging[J].      IEEE Transactions on Nuclear Science, 2023.

  1. Chang W, D'Ascenzo N, Xie Q. A relaxed      iterated Tikhonov regularization for linear ill-posed inverse problems[J].      Journal of Mathematical Analysis and Applications, 2024,      530(2): 127754.

  1. Fang L, Zhang B, Li B, Zhang X, Zhou X, Yang      J, Li A, Shi X, Liu Y, Kreissl M, D'Ascenzo N, Xiao P, Xie Q. Development      and evaluation of a new high-TOF-resolution all-digital brain PET system.      Phys Med Biol. 2023 Dec 15.

  1. Hu X, Liang X, Antonecchia E, et al. 3-D      Textural Analysis of 2-[¹⁸F] FDG PET and Ki67 Expression in Nonsmall Cell      Lung Cancer[J]. IEEE Transactions on Radiation and Plasma Medical      Sciences, 2021, 6(1): 113-120.

  1. Li J, Antonecchia E, Camerlenghi M, et al.      Correlation of [¹⁸F] florbetaben textural features and age of onset of      Alzheimer’s disease: a principal components analysis approach[J]. EJNMMI      research, 2021, 11: 1-14.

  1. Gao M, Chen H H, Chen F H, et al. First      results from all-digital PET dual heads for in-beam beam-on proton therapy      monitoring[J]. IEEE Transactions on Radiation and Plasma Medical Sciences,      2020, 5(6): 775-782.

  1. D’Ascenzo N, Antonecchia E, Gao M, et al.      Evaluation of a digital brain positron emission tomography scanner based      on the plug&imaging sensor technology[J]. IEEE Transactions on      Radiation and Plasma Medical Sciences, 2019, 4(3): 327-334.

  1. Liang X, Li J, Antonecchia E, et al.      NEMA-2008 and in-vivo animal and plant imaging performance of the large      FOV preclinical digital PET/CT system discoverist 180[J]. IEEE      Transactions on Radiation and Plasma Medical Sciences, 2020, 4(5): 622-629.

  1. D’Ascenzo N, Antonecchia E, Brensing A, et      al. A Novel High Photon Detection Efficiency Silicon Photomultiplier With      Shallow Junction in 0.35μm CMOS[J]. IEEE Electron Device Letters,      2019, 40(9): 1471-1474.

  1. Liang X, D’ascenzo N, Brockherde W, et al. Silicon      Photomultipliers With Area Up to 9 mm 2 in a 0.35-μm CMOS      Process[J]. IEEE Journal of the Electron Devices Society, 2019, 7:      239-251.

  1. D’Ascenzo N, Brockherde W, Dreiner S, et al.      Design and Characterization of a Silicon Photomultiplier in 0.35-μm       CMOS[J]. IEEE Journal of the      Electron Devices Society, 2017, 6: 74-80.