Draft:Ge Wang (scientist)

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Ge Wang (Chinese: 王 革; born in 1957) is a medical imaging scientist focusing on computed tomography(CT), artificial intelligence (AI), and deep learning.[1][2] He is Clark & Crossan Chair Professor of Biomedical Engineering and Director of the Biomedical Imaging Center[3] at Rensselaer Polytechnic Institute, Troy, New York, USA.[4][1] Wang is known for his pioneering work on CT and AI-based imaging.[5]

Career[edit]

Researcher[edit]

In the early 1990s, Wang introduced the spiral cone-beam CT method.[6][7] For this work, he was inducted into the National Academy of Inventors in 2019.[8][9][10]

Michel Defrise et al. wrote that "to solve the long-object problem, the first level of improvement with respect to the 2D filtered backprojection algorithms was obtained by backprojecting the data in 3D, along the actual measurement rays. The prototype of this approach is the algorithm of Wang et al.."[11] La Riviere and Crawford wrote that "most commercial systems used approximate methods based on extending the Feldkamp–Davis–Kress reconstruction to helical cone-beam scanning trajectories initially formulated by Wang et al."[12]

In 2016, Wang presented the deep learning-based tomographic imaging roadmap.[13][14][15][16] Wang co-authored a book on deep learning-based tomographic reconstruction[17] in 2019 with IOP Publishing.[18][19]

In partnership with General Electric, Food and Drug Administration, and Harvard University, Wang’s team develops deep imaging algorithms and systems for clinical and preclinical applications. In 2017, he was the coordinator of the first Deep Reconstruction Workshop.[20]

Wang and his collaborators developed interior tomography to solve the interior problem[21] and proposed omnitomography[22] for the spatiotemporal fusion of tomographic datasets, with simultaneous CT-MRI as an example.[23][24] Moreover, his team developed bioluminescence tomography for optical molecular imaging[25] and proposed spectrography for ultrafast and ultrafine tomography from polychromatic scattering data.[26][27] Wang worked on axiomatic bibliometrics,[28] developed the first undergraduate and graduate courses on deep medical imaging,[29] and a distanced online testing technology.[30]

Employment[edit]

Wang joined the Department of Electrical & Computer Engineering, University of Chinese Academy of Sciences as an Instructor (1984 - 1986) and became promoted to Assistant Professor (1986 - 1988).[3] He was Research Assistant (1988 - 1989) at the Department of Geography & Environmental Studies, Tasmania University, Hobart, Australia, and a Research Assistant (1989 - 1992) at the Department of Electrical & Computer Engineering, State University of New York at Buffalo, USA.[31][32]

Later, he was also an Adjunct Professor at the Department of Biomedical Engineering, Department of Mathematics, Department of Electrical and Computer Engineering, and Department of Civil Engineering at the University of Iowa, Iowa City.[31] From 1997 to 2006, Wang was the director of the CT Lab. From 2004 to 2006, he was the director of the Center for X-ray & Optical Tomography at the University of Iowa.[32]

From 2006 to 2012, Wang worked as a Pritchard Professor at the College of Engineering, Virginia Tech, Blacksburg, USA.[33] Also, he served as Adjunct Professor (2006 - 2012) at the Department of Mathematics and Department of Electrical & Computer Engineering, Virginia Tech, VA, and an Adjunct Professor (2008 - 2012)[34] with Wake Forest Institute of Regenerative Medicine, Wake Forest University, USA.[35]

Since 2013, Wang has been Clark & Crossan Endowed Chair Professor at the Department of Biomedical Engineering and Department of Electrical, Computer and Systems Engineering and Director of the Biomedical Imaging Center, School of Engineering, Center for Biotechnology and Multidisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA.[3][31]

Recognitions and Awards[edit]

Wang is a Fellow of the National Academy of Inventors (NAI) for contributions to spiral/helical cone-beam/multi-slice CT (2019).[36]

  • Herbert M. Stauffer Award, Outstanding Basic Science Paper in Academic Radiology, Association of University Radiologists, USA, 2005[37]
  • IEEE EMBS Academic Career Achievement Award 2021[38]
  • IEEE Region 1 Outstanding Teaching Award 2021[39]
  • World Artificial Intelligence Conference Youth Outstanding Paper Award 2021[40]
  • Doctoral Dissertation Award by International Neural Network Society 2021[41]
  • SPIE Aden & Marjorie Meinel Technology Achievement Award 2022[42][43][44]
  • Sigma Xi Walston Chubb Award for Innovation 2022[32][45][46][47][48]
  • 2023 William H. Wiley Distinguished Faculty Award. Rensselaer Polytechnic Institute, 2023[49]

Bibliometrics[edit]

Book[edit]

  • Machine Learning for Tomographic Imaging[17]

Selected publications[edit]

  • Wang G, Lin TH, Cheng PC, Shinozaki DM: A general cone-beam reconstruction algorithm. IEEE Trans. Med. Imaging 12:486-496, 1993.
  • Wang G, Li Y, Jiang M: Uniqueness theorems in bioluminescence tomography. Med. Phys. 31:2289-2299, 2004.[50]
  • Yu H, Wang G: Compressive sensing based interior tomography. Phys. Med. Biol. 54:2791-2805, 2009.
  • Ye YB, Yu HY, Wang G: Gel'fand-Graev'ss reconstruction formula in the 3D real space. Medical Physics, 38(S1): S69-S75, 2011.
  • Wang G, Yu H, Cong W, Katsevich A: Non-uniqueness and instability of''Ankylograph". Nature 480:E2–E3, Nov. 30, 2011.[51]
  • Katsevich G, Katsevich A, Wang G: Stability of the interior problem with polynomial attenuation in the region of interest. Inverse Problems 28:065022, 2012.
  • Stallings J, Vance E, Yang JS, Vannier MW, Liang J, Pang L, Dai L, Ye I, Wang G: Determining scientific impact using a collaboration index. PNAS 110:9680-9685, 2013.
  • Wang G, Kalra M, Murugan V, Xi Y, Gjesteby L, Getzin M, Yang QS, Cong WX, Vannier MW: Simultaneous CT-MRI: Next chapter of multi-modality imaging. Med. Phys. 42:5879-5889, 2015.[52]
  • Wang G, Perspective on deep imaging. IEEE Access, DOI:10.1109/ACCESS.2016.2624938, 2016.[13]
  • Shan HM, Padole A, Homayounieh F, Kruger U, Khera RD, Nitiwarangkul C, Kalra MK, Wang G: Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction. Nature Machine Intelligence, June 2019.[53]
  • Wang G, Ye JC, De Man B: Deep learning for tomographic image reconstruction. Nature Machine Intelligence, DOI:10.1038/s42256-020-00273-z, 2020.[15]
  • Chao HQ, Shan HM, Homayounieh F, Singh R, Khera RD, Guo HT, Su T, Wang G, Kalra MK, Yan PK: Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography. Nature Communications 12:2963 (10 pages), 2021.[54]
  • Wang G, Badal A, Jia X, Maltz JS, Mueller K, Myers KJ, Niu C, Vannier MW, Yan PK, Yu Z, Zeng RP: Development of Metaverse for Intelligent Healthcare. Nature Machine Intelligence 4:922-929.[55]
  • Wang G, Goldwag J, Wang G: DishBrain plays Pong and promises more. Nature MI, 2023[56]

References[edit]

  1. ^ a b "Inventing the future". spie.org. Retrieved 2024-01-29.
  2. ^ "How X-rays see through your skin - Ge Wang". TED-Ed. Retrieved 2024-01-29.
  3. ^ a b c "Ge Wang | Faculty". faculty.rpi.edu. Retrieved 2024-01-29.
  4. ^ Dineley, Jude (2018-08-01). "Tackling the Silent Crisis in Cancer Care". Lindau Nobel Laureate Meetings. Retrieved 2024-01-29.
  5. ^ "Ge Wang". scholar.google.com. Retrieved 2024-01-29.
  6. ^ Wang, G.; Lin, T. H.; Cheng, P.; Shinozaki, D. M. (1993). "A general cone-beam reconstruction algorithm". IEEE Transactions on Medical Imaging. 12 (3): 486–496. doi:10.1109/42.241876. ISSN 0278-0062. PMID 18218441.
  7. ^ Wang, Ge; Ye, Yangbo; Yu, Hengyong (2007-03-21). "Approximate and exact cone-beam reconstruction with standard and non-standard spiral scanning". Physics in Medicine and Biology. 52 (6): R1–13. doi:10.1088/0031-9155/52/6/R01. ISSN 0031-9155. PMID 17327647. S2CID 10502613.
  8. ^ "Ge Wang Ge Wang Named a Fellow of the National Academy of Inventors - AIMBE". Retrieved 2024-01-29.
  9. ^ Ye, Yangbo; Wang, Ge (January 2005). "Filtered backprojection formula for exact image reconstruction from cone-beam data along a general scanning curve". Medical Physics. 32 (1): 42–48. Bibcode:2005MedPh..32...42Y. doi:10.1118/1.1828673. ISSN 0094-2405. PMID 15719953.
  10. ^ Lu, Yang; Katsevich, Alexander; Zhao, Jun; Yu, Hengyong; Wang, Ge (March 2010). "Fast Exact/Quasi-Exact FBP Algorithms for Triple-Source Helical Cone-Beam CT". IEEE Transactions on Medical Imaging. 29 (3): 756–770. doi:10.1109/TMI.2009.2035617. ISSN 0278-0062. PMC 2885857. PMID 19923043.
  11. ^ Defrise, M.; Noo, F.; Kudo, H. (March 2000). "A solution to the long-object problem in helical cone-beam tomography". Physics in Medicine and Biology. 45 (3): 623–643. Bibcode:2000PMB....45..623D. doi:10.1088/0031-9155/45/3/305. ISSN 0031-9155. PMID 10730961. S2CID 250807797.
  12. ^ La Riviere, Patrick J.; Crawford, Carl R. (September 2021). "From EMI to AI: a brief history of commercial CT reconstruction algorithms". Journal of Medical Imaging (Bellingham, Wash.). 8 (5): 052111. doi:10.1117/1.JMI.8.5.052111. ISSN 2329-4302. PMC 8492478. PMID 34660842.
  13. ^ a b Wang, Ge (2016). "A Perspective on Deep Imaging". IEEE Access. 4: 8914–8924. Bibcode:2016IEEEA...4.8914W. doi:10.1109/ACCESS.2016.2624938. Retrieved 2024-01-29.
  14. ^ Shan, Hongming; Padole, Atul; Homayounieh, Fatemeh; Kruger, Uwe; Khera, Ruhani Doda; Nitiwarangkul, Chayanin; Kalra, Mannudeep K.; Wang, Ge (June 2019). "Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction". Nature Machine Intelligence. 1 (6): 269–276. doi:10.1038/s42256-019-0057-9. ISSN 2522-5839. PMC 7687920. PMID 33244514.
  15. ^ a b Wang, Ge; Ye, Jong Chul; De Man, Bruno (December 2020). "Deep learning for tomographic image reconstruction". Nature Machine Intelligence. 2 (12): 737–748. doi:10.1038/s42256-020-00273-z. ISSN 2522-5839. S2CID 230617617.
  16. ^ Chao, Hanqing; Shan, Hongming; Homayounieh, Fatemeh; Singh, Ramandeep; Khera, Ruhani Doda; Guo, Hengtao; Su, Timothy; Wang, Ge; Kalra, Mannudeep K.; Yan, Pingkun (2021-05-20). "Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography". Nature Communications. 12 (1): 2963. arXiv:2008.06997. Bibcode:2021NatCo..12.2963C. doi:10.1038/s41467-021-23235-4. ISSN 2041-1723. PMC 8137697. PMID 34017001.
  17. ^ a b ShieldSquare Captcha. IOP. December 2019. ISBN 978-0-7503-2216-4. Retrieved 2024-01-29. {{cite book}}: |website= ignored (help)
  18. ^ Wang, Ge; Ye, Jong Chu; Mueller, Klaus; Fessler, Jeffrey A. (2018). "Image Reconstruction is a New Frontier of Machine Learning". IEEE Transactions on Medical Imaging. 37 (6): 1289–1296. doi:10.1109/TMI.2018.2833635. PMID 29870359. Retrieved 2024-01-29.
  19. ^ Wang, Ge; Jacob, Mathews; Mou, Xuanqin; Shi, Yongyi; Eldar, Yonina C. (2021). "Deep Tomographic Image Reconstruction: Yesterday, Today, and Tomorrow—Editorial for the 2nd Special Issue "Machine Learning for Image Reconstruction"". IEEE Transactions on Medical Imaging. 40 (11): 2956–2964. doi:10.1109/TMI.2021.3115547. Retrieved 2024-01-29.
  20. ^ Opening Remarks by Dr. Chi Liu, retrieved 2024-01-29
  21. ^ Wang, Ge; Yu, Hengyong (2013-08-21). "Meaning of Interior Tomography". Physics in Medicine and Biology. 58 (16): R161–R186. arXiv:1304.7823. Bibcode:2013PMB....58R.161W. doi:10.1088/0031-9155/58/16/R161. ISSN 0031-9155. PMC 3775479. PMID 23912256.
  22. ^ Wang, Ge; Zhang, Jie; Gao, Hao; Weir, Victor; Yu, Hengyong; Cong, Wenxiang; Xu, Xiaochen; Shen, Haiou; Bennett, James; Furth, Mark; Wang, Yue; Vannier, Michael (29 June 2012). "Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography". PLOS ONE. 7 (6): e39700. Bibcode:2012PLoSO...739700W. doi:10.1371/journal.pone.0039700. ISSN 1932-6203. PMC 3387257. PMID 22768108.
  23. ^ Wang, Ge; Kalra, Mannudeep; Murugan, Venkatesh; Xi, Yan; Gjesteby, Lars; Getzin, Matthew; Yang, Qingsong; Cong, Wenxiang; Vannier, Michael (October 2015). "Vision 20/20: Simultaneous CT-MRI--Next chapter of multimodality imaging". Medical Physics. 42 (10): 5879–5889. Bibcode:2015MedPh..42.5879W. doi:10.1118/1.4929559. ISSN 2473-4209. PMID 26429262.
  24. ^ Peng, Yuting; Li, Mengzhou; Grandinetti, Jace; Wang, Ge; Jia, Xun (2022). "Top-Level Design and Simulated Performance of the First Portable CT-MR Scanner". IEEE Access. 10: 102325–102333. arXiv:2203.15989. Bibcode:2022IEEEA..10j2325P. doi:10.1109/ACCESS.2022.3208278. Retrieved 2024-01-29.
  25. ^ Wang, Ge; Cong, Wenxiang; Durairaj, Kumar; Qian, Xin; Shen, Haiou; Sinn, Patrick; Hoffman, Eric; McLennan, Geoffrey; Henry, Michael (2006-08-21). "In vivo mouse studies with bioluminescence tomography". Optics Express. 14 (17): 7801–7809. Bibcode:2006OExpr..14.7801W. doi:10.1364/oe.14.007801. ISSN 1094-4087. PMID 19529149.
  26. ^ Wang, Ge; Yu, Hengyong; Cong, Wenxiang; Katsevich, Alexander (December 2011). "Non-uniqueness and instability of 'ankylography'". Nature. 480 (7375): E2–E3. Bibcode:2011Natur.480E...2W. doi:10.1038/nature10635. ISSN 1476-4687. PMID 22129733. S2CID 4419783.
  27. ^ "Three-dimensional technique on trial" (PDF).
  28. ^ Stallings, Jonathan; Vance, Eric; Yang, Jiansheng; Vannier, Michael W.; Liang, Jimin; Pang, Liaojun; Dai, Liang; Ye, Ivan; Wang, Ge (2013-06-11). "Determining scientific impact using a collaboration index". Proceedings of the National Academy of Sciences of the United States of America. 110 (24): 9680–9685. Bibcode:2013PNAS..110.9680S. doi:10.1073/pnas.1220184110. ISSN 0027-8424. PMC 3683734. PMID 23720314.
  29. ^ Wiedeman, Christopher; Xie, Huidong; Mou, Xuanqin; Wang, Ge (2020-12-01). "Innovating the Medical Imaging Course". Technology & Innovation. 21 (4): 1–11. doi:10.21300/21.4.2020.5. S2CID 234566259.
  30. ^ Li, Mengzhou; Luo, Lei; Sikdar, Sujoy; Nizam, Navid Ibtehaj; Gao, Shan; Shan, Hongming; Kruger, Melanie; Kruger, Uwe; Mohamed, Hisham; Xia, Lirong; Wang, Ge (2021-03-01). "Optimized collusion prevention for online exams during social distancing". npj Science of Learning. 6 (1): 5. Bibcode:2021npjSL...6....5L. doi:10.1038/s41539-020-00083-3. ISSN 2056-7936. PMC 7921656. PMID 33649355.
  31. ^ a b c "dblp: Ge Wang 0001". dblp.org. Retrieved 2024-01-29.
  32. ^ a b c "Speaker". IFoRE. Retrieved 2024-01-29.
  33. ^ "Ge Wang named Samuel Reynolds Pritchard Professor of Engineering". news.vt.edu. Retrieved 2024-01-30.
  34. ^ Gaines, Dr Tyeese L. (January 2011). "New study: No racial bias against black scientists". TheGrio. Retrieved 2024-01-30.
  35. ^ "Ge Wang and colleagues refute a study on 'racial bias' report in NIH research awards". news.vt.edu. Retrieved 2024-01-30.
  36. ^ "About the NAI Fellows Program". NAI. Retrieved 2024-01-29.
  37. ^ "Honors and Awards of Ming Jiang". www.math.pku.edu.cn. Retrieved 2024-01-29.
  38. ^ "Ge Wang Receives 2021 EMBS Academic Career Achievement Award | News". news.rpi.edu. Retrieved 2024-01-30.
  39. ^ "2021 IEEE REGION 1 MAJOR AWARDS RELEASED! | IEEE Region 1". 2021-10-10. Retrieved 2024-01-30.
  40. ^ Shan, Hongming; Padole, Atul; Homayounieh, Fatemeh; Kruger, Uwe; Khera, Ruhani Doda; Nitiwarangkul, Chayanin; Kalra, Mannudeep K.; Wang, Ge (June 2019). "Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction". Nature Machine Intelligence. 1 (6): 269–276. doi:10.1038/s42256-019-0057-9. ISSN 2522-5839. PMC 7687920. PMID 33244514.
  41. ^ "Student Receives International Neural Network Society Doctoral Dissertation Award | Biomedical Engineering". bme.rpi.edu. Retrieved 2024-01-30.
  42. ^ "Medical Imaging Expert Ge Wang Honored by International Society for Optics and Photonics | News". news.rpi.edu. Retrieved 2024-01-30.
  43. ^ "Ge Wang: The SPIE Aden & Marjorie Meinel Technology Achievement Award". spie.org. Retrieved 2024-01-30.
  44. ^ "SPIE Aden and Marjorie Meinel Technology Achievement Award". spie.org. Retrieved 2024-01-30.
  45. ^ "Speaker". IFoRE. Retrieved 2024-01-30.
  46. ^ "Announcing the 2022 Sigma Xi Award Winners". www.sigmaxi.org. Retrieved 2024-01-30.
  47. ^ "Announcing the 2022 Sigma Xi Award Winners". www.sigmaxi.org. Retrieved 2024-01-30.
  48. ^ Future of Medical Imaging – Sigma Xi Walston Chubb Innovation Award Presentation by Ge Wang, retrieved 2024-01-30
  49. ^ "More Than 1,900 Degrees To Be Awarded at 217th Rensselaer Polytechnic Institute Commencement Ceremony | News". news.rpi.edu. Retrieved 2024-01-30.
  50. ^ Wang, Ge; Cong, Wenxiang; Durairaj, Kumar; Qian, Xin; Shen, Haiou; Sinn, Patrick; Hoffman, Eric; McLennan, Geoffrey; Henry, Michael (2006-08-21). "In vivo mouse studies with bioluminescence tomography". Optics Express. 14 (17): 7801–7809. Bibcode:2006OExpr..14.7801W. doi:10.1364/oe.14.007801. ISSN 1094-4087. PMID 19529149.
  51. ^ Wang, Ge; Yu, Hengyong; Cong, Wenxiang; Katsevich, Alexander (December 2011). "Non-uniqueness and instability of 'ankylography'". Nature. 480 (7375): E2–E3. Bibcode:2011Natur.480E...2W. doi:10.1038/nature10635. ISSN 1476-4687. PMID 22129733. S2CID 4419783.
  52. ^ Wang, Ge; Kalra, Mannudeep; Murugan, Venkatesh; Xi, Yan; Gjesteby, Lars; Getzin, Matthew; Yang, Qingsong; Cong, Wenxiang; Vannier, Michael (October 2015). "Vision 20/20: Simultaneous CT-MRI--Next chapter of multimodality imaging". Medical Physics. 42 (10): 5879–5889. Bibcode:2015MedPh..42.5879W. doi:10.1118/1.4929559. ISSN 2473-4209. PMID 26429262.
  53. ^ Shan, Hongming; Padole, Atul; Homayounieh, Fatemeh; Kruger, Uwe; Khera, Ruhani Doda; Nitiwarangkul, Chayanin; Kalra, Mannudeep K.; Wang, Ge (June 2019). "Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction". Nature Machine Intelligence. 1 (6): 269–276. doi:10.1038/s42256-019-0057-9. ISSN 2522-5839. PMC 7687920. PMID 33244514.
  54. ^ Chao, Hanqing; Shan, Hongming; Homayounieh, Fatemeh; Singh, Ramandeep; Khera, Ruhani Doda; Guo, Hengtao; Su, Timothy; Wang, Ge; Kalra, Mannudeep K.; Yan, Pingkun (2021-05-20). "Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography". Nature Communications. 12 (1): 2963. arXiv:2008.06997. Bibcode:2021NatCo..12.2963C. doi:10.1038/s41467-021-23235-4. ISSN 2041-1723. PMC 8137697. PMID 34017001.
  55. ^ Wang, Ge; Badal, Andreu; Jia, Xun; Maltz, Jonathan S.; Mueller, Klaus; Myers, Kyle J.; Niu, Chuang; Vannier, Michael; Yan, Pingkun; Yu, Zhou; Zeng, Rongping (November 2022). "Development of metaverse for intelligent healthcare". Nature Machine Intelligence. 4 (11): 922–929. doi:10.1038/s42256-022-00549-6. ISSN 2522-5839. PMC 10015955. PMID 36935774.
  56. ^ Goldwag, Joshua; Wang, Ge (June 2023). "DishBrain plays Pong and promises more". Nature Machine Intelligence. 5 (6): 568–569. doi:10.1038/s42256-023-00666-w. ISSN 2522-5839. S2CID 259034150.
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