| 词条 | Dorin Comaniciu |
| 释义 |
| name = Dorin Comaniciu | birth_date = {{birth year and age|1964}} | birth_place = {{flagicon|Romania}} Fagaras, Romania | residence = {{flagicon|USA}} New Jersey, United States | field = Machine Intelligence, Diagnostic Imaging, Image-Guided Surgery, Computer Vision | work_institution = Siemens, Siemens Healthcare | awards = Longuet-Higgins Prize (2010), IEEE Fellow (2012), ACM Fellow (2017) | website = {{URL|http://comaniciu.net}} }} Dorin Comaniciu (born 1964) is a Romanian-American computer scientist, Senior Vice President of Artificial Intelligence and Digital Innovation at Siemens Healthcare. ResearchComaniciu is best known for his work in computer vision,[1][2] medical imaging[3] and machine learning.[4][5] His academic publications have 42,000 citations.[6] As of 2019 he holds 243 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 is focused on artificial intelligence,[13][14][15] hyper-realistic visualization,[16] and precision medicine.[17] Together with his team and clinical collaborators he helped pioneer multiple 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. EducationComaniciu studied for a PhD in electronics and telecommunications at the Polytechnic University of Bucharest, which was awarded in 1995 and supervised by Victor Neagoe. In 1999 he received a second PhD in electrical and computer engineering, with the thesis on robust statistics for computer vision, from Rutgers University under the supervision of Peter Meer. In 2011 he graduated the Advanced Management Program at the University of Pennsylvania's Wharton School. Awards and honors
References1. ^Mean shift: a robust approach toward feature space analysis, IEEE PAMI 2002 {{Authority control}}{{DEFAULTSORT:Comaniciu, Dorin}}2. ^Kernel-based object tracking, IEEE PAMI 2003 3. ^Shaping the future through innovations: From medical imaging to precision medicine, Medical Image Analyis, Vol 33, pp 19-26, 2016 4. ^[https://www.springer.com/us/book/9781493905997 Marginal Space Learning for Medical Image Analysis, ] Springer, 2014 5. ^Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing, IEEE TMI, 2016 6. ^[https://scholar.google.com/citations?user=-XZ2HrAAAAAJ Publications according to Google Scholar] 7. ^US Patents of Dorin Comaniciu 8. ^[https://worldwide.espacenet.com/searchResults?DB=EPODOC&IN=%22Dorin+Comaniciu%22%20or%20%22Comaniciu+Dorin%22 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. ^[https://www.dotmed.com/legal/print/story.html?nid=1962 Siemens Showcases a New Level of Echocardiography], DOTmed, 2006 12. ^Getting to the Heart of Visualization, R&D Magazine, 2015 13. ^[https://link.springer.com/chapter/10.1007/978-3-319-46726-9_27 An Artificial Agent for Anatomical Landmark Detection in Medical Images], MICCAI 2016 14. ^[https://arxiv.org/abs/1611.10336 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. ^[https://undark.org/article/medical-imaging-cinematic-rendering/ Medical Imaging Goes to the Movies], Undark 2016 17. ^{{Cite journal|last=Kayvanpour|first=Elham|last2=Mansi|first2=Tommaso|last3=Sedaghat-Hamedani|first3=Farbod|last4=Amr|first4=Ali|last5=Neumann|first5=Dominik|last6=Georgescu|first6=Bogdan|last7=Seegerer|first7=Philipp|last8=Kamen|first8=Ali|last9=Haas|first9=Jan|date=2015-07-31|title=Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart|journal=PLOS ONE|volume=10|issue=7|pages=e0134869|doi=10.1371/journal.pone.0134869|pmid=26230546|pmc=4521877|issn=1932-6203}} 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. ^[https://www.itnonline.com/content/fda-clears-compressed-sensing-mri-acceleration-technology-siemens-healthineers Compressed Sensing], Imaging Technology News, 2017 22. ^AIMBE citation 23. ^MICCAI citation 24. ^{{citation|url=https://www.acm.org/media-center/2017/december/fellows-2017|title=ACM Recognizes 2017 Fellows for Making Transformative Contributions and Advancing Technology in the Digital Age|publisher=Association for Computing Machinery|date=December 11, 2017|accessdate=2017-11-13}} 7 : 1964 births|Living people|Computer vision researchers|Fellow Members of the IEEE|Wharton School of the University of Pennsylvania alumni|Fellows of the American Institute for Medical and Biological Engineering|Fellows of the Association for Computing Machinery |
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