Biography:Dorin Comaniciu

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Short description: Romanian-American computer scientist
Dorin Comaniciu
Born
Făgăraș, Romania
AwardsLonguet-Higgins Prize (2010), IEEE Fellow (2012), ACM Fellow (2017), Elected to National Academy of Medicine (2019)
Scientific career
FieldsMachine Intelligence, Diagnostic Imaging, Image-Guided Surgery, Computer Vision
InstitutionsSiemens, Siemens Healthcare
Websitecomaniciu.net

Dorin Comaniciu (born 1964) is a Romanian-American computer scientist. He is the Senior Vice President of Artificial Intelligence and Digital Innovation at Siemens Healthcare.

Research

Comaniciu is known for his work in computer vision,[1][2] medical imaging[3] and machine learning.[4][5] His academic publications have 54,000 citations with an H-index of 85.[6] As of 2022, he holds 308 US patents[7] and 550 international patent applications.[8] He joined Siemens in 1999 as a senior research scientist with a focus on computer vision applications for automotive systems.[9] Since 2004, he has served in various research and leadership positions, directing technology development in diagnostic imaging[10][11] and image-guided surgery[12]

Most recently, his team's research has focused on artificial intelligence,[13][14][15] hyper-realistic visualization,[16] and precision medicine.[17]

Together with his team and clinical collaborators, he has helped pioneer many clinical products, including efficient bone reading,[18] vascular analysis, cardiac function assessment, trans-esophageal 3D heart valve assessment,[19] guidance for aortic valve implantation,[20] enhanced stent visualization, compressed sensing for Magnetic Resonance,[21] and automatic patient positioning for Computed Tomography.

Awards and honors

  • Institute of Electrical and Electronics Engineers (IEEE) Conference on Computer Vision and Pattern Recognition (CVPR) Best Paper Award 2000 (together with Visvanathan Ramesh and Peter Meer)
  • IEEE Longuet-Higgins Prize 2010, for 'Fundamental contributions in Computer Vision'
  • IEEE Fellow 2012, for contributions to medical image analysis and computer vision
  • American Institute for Medical and Biological Engineering (AIMBE) Fellow 2013, for technical contributions to medical imaging using machine learning, and for leadership in imaging technology[22]
  • Medical Image Computing and Computer-Assisted Interventions (MICCAI) Society Fellow 2015, for contributions to the theory and practice of medical imaging and image-guided interventions[23]
  • Association for Computing Machinery (ACM) Fellow 2017, for contributions to machine intelligence, diagnostic imaging, image-guided interventions, and computer vision[24]
  • Honorary doctorate awarded in 2018 from Titu Maiorescu University, Romania
  • Member of the National Academy of Medicine 2019[25]

References

  1. Mean shift: a robust approach toward feature space analysis, IEEE PAMI 2002
  2. Kernel-based object tracking, IEEE PAMI 2003
  3. Shaping the future through innovations: From medical imaging to precision medicine, Medical Image Analysis, Vol 33, pp 19-26, 2016
  4. Marginal Space Learning for Medical Image Analysis, Springer, 2014
  5. Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing, IEEE TMI, 2016
  6. Publications according to Google Scholar
  7. US Patents of Dorin Comaniciu
  8. Worldwide Patents of Dorin Comaniciu
  9. Reliable Detection of Overtaking Vehicles Using Robust Information Fusion, IEEE Transactions on Intelligent Transportation Systems, 2006
  10. Princeton inventor refines computer vision technology for doctors, wins recognition for work, NJ.COM, 2011
  11. Siemens Showcases a New Level of Echocardiography, DOTmed, 2006
  12. Getting to the Heart of Visualization, R&D Magazine, 2015
  13. An Artificial Agent for Anatomical Landmark Detection in Medical Images, MICCAI 2016
  14. An Artificial Agent for Robust Image Registration, AAAI 2017
  15. Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans, IEEE PAMI 2018
  16. Medical Imaging Goes to the Movies, Undark 2016
  17. Kayvanpour, Elham; Mansi, Tommaso; Sedaghat-Hamedani, Farbod; Amr, Ali; Neumann, Dominik; Georgescu, Bogdan; Seegerer, Philipp; Kamen, Ali et al. (2015-07-31). "Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart". PLOS ONE 10 (7): e0134869. doi:10.1371/journal.pone.0134869. ISSN 1932-6203. PMID 26230546. Bibcode2015PLoSO..1034869K. 
  18. Bone Reading, British Institute of Radiology, 2017
  19. Patient-Specific Modeling and Quantification of the Aortic and Mitral Valves From 4-D Cardiac CT and TEE, IEEE TMI, 2010
  20. Siemens Wins 2010 Techno-College Innovation Award, European Association for Cardio-Thoracic Surgery
  21. Compressed Sensing, Imaging Technology News, 2017
  22. AIMBE citation
  23. title MICCAI Fellows
  24. ACM Recognizes 2017 Fellows for Making Transformative Contributions and Advancing Technology in the Digital Age, Association for Computing Machinery, December 11, 2017, https://www.acm.org/media-center/2017/december/fellows-2017, retrieved 2017-11-13 
  25. National Academy of Medicine Elects 100 New Members/, 21 October 2019, https://nam.edu/national-academy-of-medicine-elects-100-new-members, retrieved 6 January 2020