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Fang Liu, Ph.D.

Title
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Department
Address
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Biography
University of Wisconsin-Madison, USAAssistant Scientist12/2019Radiology
University of Wisconsin-Madison, USAPh.D.10/2015Medical Physics
University of Western Ontario, CanadaM.Sc.08/2011Medical Biophysics
Sun Yat-Sen University, ChinaB.Sc.10/2008Biomedical Engineering
2019
Magnetic Resonance in Medicine Editor's Pick
2018
ISMRM Junior Fellow Award
2018
The Oral Presentation 1st place, ISMRM Machine Learning Workshop II
2018
Magnetic Resonance in Medicine Distinguished Reviewer
2018
Magnetic Resonance in Medicine Editor's Pick
2017
Journal of Magnetic Resonance Imaging Distinguished Reviewer
2017
OCSMRM Young Investigator Award
2016
ISMRM Merit Award - Magna Cum Laude
2015 - 2017
Clinical Biomechanics Award
2014 - 2019
ISMRM Merit Award - Summa Cum Laude

Overview
Dr. Liu is an Assistant Professor at Harvard University. He is currently working in the Department of Radiology, Massachusetts General Hospital, Harvard Medical School. His research focuses on medical image acquisition and reconstruction, image analysis and processing, and physiological modeling, pertaining to magnetic resonance (MR) imaging, molecular imaging, and optical imaging. His recent interest also includes the development of artificial intelligence methods towards improving imaging speed and robustness and automating clinical imaging workflow. Before joining Harvard in 2020, Dr. Liu was an Assistant Scientist at Radiology, University of Wisconsin-Madison, from 2015 to 2019 working on translational imaging projects spanning several clinical topics. In 2015, he received his Ph.D. from Medical Physics, University of Wisconsin-Madison, where his research focused on developing new MR pulse sequences and optimizing imaging biomarkers for improved assessment of musculoskeletal and neural tissue. In 2011, he received his M.Sc. from Medical Biophysics, Western University, Canada, where his research focused on improving breast MR imaging using machine learning. In 2008, he received B.Sc. from Biomedical Engineering, Sun Yat-sen University, China.

Bibliographic
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
  1. Feng L, Ma D, Liu F. Rapid MR relaxometry using deep learning: An overview of current techniques and emerging trends. NMR Biomed. 2020 Oct 15; e4416. PMID: 33063400.
    Citations:    Fields:    
  2. Liu F. Improving Quantitative Magnetic Resonance Imaging Using Deep Learning. Semin Musculoskelet Radiol. 2020 Aug; 24(4):451-459. PMID: 32992372.
    Citations:    Fields:    
  3. Liu F, Kijowski R, Feng L, El Fakhri G. High-performance rapid MR parameter mapping using model-based deep adversarial learning. Magn Reson Imaging. 2020 Sep 25; 74:152-160. PMID: 32980503.
    Citations:    Fields:    
  4. Loegering IF, Denning SC, Johnson KM, Liu F, Lee KS, Thelen DG. Ultrashort echo time (UTE) imaging reveals a shift in bound water that is sensitive to sub-clinical tendinopathy in older adults. Skeletal Radiol. 2020 Jul 08. PMID: 32642791.
    Citations:    Fields:    
  5. Mei X, Lee HC, Diao KY, Huang M, Lin B, Liu C, Xie Z, Ma Y, Robson PM, Chung M, Bernheim A, Mani V, Calcagno C, Li K, Li S, Shan H, Lv J, Zhao T, Xia J, Long Q, Steinberger S, Jacobi A, Deyer T, Luksza M, Liu F, Little BP, Fayad ZA, Yang Y. Artificial intelligence-enabled rapid diagnosis of patients with COVID-19. Nat Med. 2020 08; 26(8):1224-1228. PMID: 32427924.
    Citations: 24     Fields:    Translation:HumansCellsPHPublic Health
  6. Guan B, Liu F, Haj-Mirzaian A, Demehri S, Samsonov A, Neogi T, Guermazi A, Kijowski R. Deep learning risk assessment models for predicting progression of radiographic medial joint space loss over a 48-MONTH follow-up period. Osteoarthritis Cartilage. 2020 04; 28(4):428-437. PMID: 32035934.
    Citations:    Fields:    
  7. Kijowski R, Liu F, Caliva F, Pedoia V. Deep learning for lesion detection, progression, and prediction of musculoskeletal disease. J Magn Reson Imaging. 2019 Nov 25. PMID: 31763739.
    Citations: 1     Fields:    
  8. Feng L, Wen Q, Huang C, Tong A, Liu F, Chandarana H. GRASP-Pro: imProving GRASP DCE-MRI through self-calibrating subspace-modeling and contrast phase automation. Magn Reson Med. 2020 01; 83(1):94-108. PMID: 31400028.
    Citations: 1     Fields:    
  9. Liu F, Samsonov A, Chen L, Kijowski R, Feng L. SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction. Magn Reson Med. 2019 11; 82(5):1890-1904. PMID: 31166049.
    Citations: 4     Fields:    Translation:Humans
  10. Liu F, Guan B, Zhou Z, Samsonov A, Rosas H, Lian K, Sharma R, Kanarek A, Kim J, Guermazi A, Kijowski R. Fully Automated Diagnosis of Anterior Cruciate Ligament Tears on Knee MR Images by Using Deep Learning. Radiol Artif Intell. 2019 May 08; 1(3):180091. PMID: 32076658.
    Citations: 4     
  11. Kijowski R, Thurlow P, Blankenbaker D, Liu F, McGuine T, Li G, Tuite M. Preoperative MRI Shoulder Findings Associated with Clinical Outcome 1 Year after Rotator Cuff Repair. Radiology. 2019 06; 291(3):722-729. PMID: 31012813.
    Citations:    Fields:    Translation:Humans
  12. Zha W, Fain SB, Schiebler ML, Evans MD, Nagle SK, Liu F. Deep convolutional neural networks with multiplane consensus labeling for lung function quantification using UTE proton MRI. J Magn Reson Imaging. 2019 10; 50(4):1169-1181. PMID: 30945385.
    Citations: 1     Fields:    Translation:Humans
  13. Liu F, Feng L, Kijowski R. MANTIS: Model-Augmented Neural neTwork with Incoherent k-space Sampling for efficient MR parameter mapping. Magn Reson Med. 2019 07; 82(1):174-188. PMID: 30860285.
    Citations: 3     Fields:    Translation:Humans
  14. Samsonov A, Liu F, Velikina JV. Resolving estimation uncertainties of chemical shift encoded fat-water imaging using magnetization transfer effect. Magn Reson Med. 2019 07; 82(1):202-212. PMID: 30847974.
    Citations:    Fields:    Translation:Humans
  15. Liu F, Yadav P, Baschnagel AM, McMillan AB. MR-based treatment planning in radiation therapy using a deep learning approach. J Appl Clin Med Phys. 2019 Mar; 20(3):105-114. PMID: 30861275.
    Citations: 2     Fields:    Translation:Humans
  16. Liu F. SUSAN: segment unannotated image structure using adversarial network. Magn Reson Med. 2019 05; 81(5):3330-3345. PMID: 30536427.
    Citations: 6     Fields:    Translation:Humans
  17. Liu F, Jang H, Kijowski R, Zhao G, Bradshaw T, McMillan AB. A deep learning approach for 18F-FDG PET attenuation correction. EJNMMI Phys. 2018 Nov 12; 5(1):24. PMID: 30417316.
    Citations: 12     
  18. Nguyen JC, Allen H, Liu F, Woo KM, Zhou Z, Kijowski R. Maturation-Related Changes in T2 Relaxation Times of Cartilage and Meniscus of the Pediatric Knee Joint at 3 T. AJR Am J Roentgenol. 2018 12; 211(6):1369-1375. PMID: 30299996.
    Citations:    Fields:    Translation:Humans
  19. Bradshaw TJ, Zhao G, Jang H, Liu F, McMillan AB. Feasibility of Deep Learning-Based PET/MR Attenuation Correction in the Pelvis Using Only Diagnostic MR Images. Tomography. 2018 Sep; 4(3):138-147. PMID: 30320213.
    Citations: 5     Fields:    
  20. Liu F, Zhou Z, Samsonov A, Blankenbaker D, Larison W, Kanarek A, Lian K, Kambhampati S, Kijowski R. Deep Learning Approach for Evaluating Knee MR Images: Achieving High Diagnostic Performance for Cartilage Lesion Detection. Radiology. 2018 10; 289(1):160-169. PMID: 30063195.
    Citations: 13     Fields:    Translation:Humans
  21. Zhou Z, Zhao G, Kijowski R, Liu F. Deep convolutional neural network for segmentation of knee joint anatomy. Magn Reson Med. 2018 12; 80(6):2759-2770. PMID: 29774599.
    Citations: 16     Fields:    Translation:Humans
  22. Jang H, Liu F, Zhao G, Bradshaw T, McMillan AB. Technical Note: Deep learning based MRAC using rapid ultrashort echo time imaging. Med Phys. 2018 May 15. PMID: 29763997.
    Citations: 8     Fields:    
  23. Nguyen JC, Liu F, Blankenbaker DG, Woo KM, Kijowski R. Juvenile Osteochondritis Dissecans: Cartilage T2 Mapping of Stable Medial Femoral Condyle Lesions. Radiology. 2018 08; 288(2):536-543. PMID: 29762089.
    Citations: 3     Fields:    Translation:Humans
  24. Zhao G, Liu F, Oler JA, Meyerand ME, Kalin NH, Birn RM. Bayesian convolutional neural network based MRI brain extraction on nonhuman primates. Neuroimage. 2018 07 15; 175:32-44. PMID: 29604454.
    Citations: 7     Fields:    Translation:Animals
  25. Zha W, Kruger SJ, Johnson KM, Cadman RV, Bell LC, Liu F, Hahn AD, Evans MD, Nagle SK, Fain SB. Pulmonary ventilation imaging in asthma and cystic fibrosis using oxygen-enhanced 3D radial ultrashort echo time MRI. J Magn Reson Imaging. 2018 05; 47(5):1287-1297. PMID: 29086454.
    Citations: 5     Fields:    Translation:Humans
  26. Jang H, Liu F, Bradshaw T, McMillan AB. Rapid dual-echo ramped hybrid encoding MR-based attenuation correction (dRHE-MRAC) for PET/MR. Magn Reson Med. 2018 06; 79(6):2912-2922. PMID: 28971513.
    Citations: 8     Fields:    Translation:Humans
  27. Liu F, Jang H, Kijowski R, Bradshaw T, McMillan AB. Deep Learning MR Imaging-based Attenuation Correction for PET/MR Imaging. Radiology. 2018 02; 286(2):676-684. PMID: 28925823.
    Citations: 41     Fields:    Translation:Humans
  28. Liu F, Zhou Z, Jang H, Samsonov A, Zhao G, Kijowski R. Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging. Magn Reson Med. 2018 04; 79(4):2379-2391. PMID: 28733975.
    Citations: 30     Fields:    Translation:Humans
  29. Kijowski R, Rosas H, Williams A, Liu F. MRI characteristics of torn and untorn post-operative menisci. Skeletal Radiol. 2017 Oct; 46(10):1353-1360. PMID: 28653078.
    Citations: 2     Fields:    Translation:Humans
  30. Liu F, Kijowski R. Assessment of different fitting methods for in-vivo bi-component T2* analysis of human patellar tendon in magnetic resonance imaging. Muscles Ligaments Tendons J. 2017 Jan-Mar; 7(1):163-172. PMID: 28717625.
    Citations: 4     
  31. Kijowski R, Wilson JJ, Liu F. Bicomponent ultrashort echo time T2* analysis for assessment of patients with patellar tendinopathy. J Magn Reson Imaging. 2017 11; 46(5):1441-1447. PMID: 28263448.
    Citations: 7     Fields:    Translation:Humans
  32. Liu F, Velikina JV, Block WF, Kijowski R, Samsonov AA. Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model. IEEE Trans Med Imaging. 2017 02; 36(2):527-537. PMID: 28113746.
    Citations: 4     Fields:    
  33. Kijowski R, Rosas H, Samsonov A, King K, Peters R, Liu F. Knee imaging: Rapid three-dimensional fast spin-echo using compressed sensing. J Magn Reson Imaging. 2017 06; 45(6):1712-1722. PMID: 27726244.
    Citations: 6     Fields:    Translation:Humans
  34. Buchanan KA, Maza M, Pérez-Vázquez CE, Yen TY, Kijowski R, Liu F, Radwin RG. Proximal forearm extensor muscle strain is reduced when driving nails using a shock-controlled hammer. Clin Biomech (Bristol, Avon). 2016 10; 38:22-8. PMID: 27542101.
    Citations:    Fields:    Translation:Humans
  35. Kaiser J, Vignos MF, Liu F, Kijowski R, Thelen DG. American Society of Biomechanics Clinical Biomechanics Award 2015: MRI assessments of cartilage mechanics, morphology and composition following reconstruction of the anterior cruciate ligament. Clin Biomech (Bristol, Avon). 2016 05; 34:38-44. PMID: 27061359.
    Citations: 8     Fields:    Translation:Humans
  36. Liu F, Chaudhary R, Block WF, Samsonov A, Kijowski R. Multicomponent T2 analysis of articular cartilage with synovial fluid partial volume correction. J Magn Reson Imaging. 2016 May; 43(5):1140-7. PMID: 26435385.
    Citations: 4     Fields:    Translation:Humans
  37. Liu F, Choi KW, Samsonov A, Spencer RG, Wilson JJ, Block WF, Kijowski R. Articular Cartilage of the Human Knee Joint: In Vivo Multicomponent T2 Analysis at 3.0 T. Radiology. 2015 Nov; 277(2):477-88. PMID: 26024307.
    Citations: 5     Fields:    Translation:Humans
  38. Liu F, Block WF, Kijowski R, Samsonov A. Rapid multicomponent relaxometry in steady state with correction of magnetization transfer effects. Magn Reson Med. 2016 Apr; 75(4):1423-33. PMID: 25959974.
    Citations: 12     Fields:    Translation:Humans
  39. Liu F, Samsonov A, Wilson JJ, Blankenbaker DG, Block WF, Kijowski R. Rapid in vivo multicomponent T2 mapping of human knee menisci. J Magn Reson Imaging. 2015 Nov; 42(5):1321-8. PMID: 25847733.
    Citations: 2     Fields:    Translation:Humans
  40. Liu F, Chaudhary R, Hurley SA, Munoz Del Rio A, Alexander AL, Samsonov A, Block WF, Kijowski R. Rapid multicomponent T2 analysis of the articular cartilage of the human knee joint at 3.0T. J Magn Reson Imaging. 2014 May; 39(5):1191-7. PMID: 24115518.
    Citations: 22     Fields:    Translation:Humans
  41. Li F, Huang XP, Wang ZQ, Liu FR, Zhou XH, Zhong L, Wu ZQ, Han XQ, Zhu MG, Zhao T. [Expression of miR-9 in B lymphocytes and B cell lymphomas cell lines and its significance]. Zhonghua Xue Ye Xue Za Zhi. 2011 Apr; 32(4):249-53. PMID: 21569708.
    Citations: 1     Fields:    Translation:HumansCells
  42. Liu F, Kornecki A, Shmuilovich O, Gelman N. Optimization of time-to-peak analysis for differentiating malignant and benign breast lesions with dynamic contrast-enhanced MRI. Acad Radiol. 2011 Jun; 18(6):694-704. PMID: 21420329.
    Citations: 1     Fields:    Translation:Humans
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.