Baojun Li, PhD

Research Associate Professor, Radiology

Baojun Li
85 E. Concord St


Baojun Li received his Ph.D. from The University of Iowa in 2004 (Advisors: Prof. Joe Reinhardt, Prof. Gary Christensen). His dissertation was on 3D Nonlinear Image Registration and Warping of Pulmonary CT for Lung Atlas and Radiation Treatment Planning. From 2002 to 2009, he worked as a Senior Scientist at GE Healthcare’s Applied Science Lab, where he was awarded multiple GE Management Awards for his contributions to the development of Radiographic Tomosynthesis, Low-dose CT (aka. ASiR), and Dual-energy CT (aka. Gem Stone Imaging). Baojun currently serves as an Associate Editor for for Medical Physics Journal and OMICS Journal of Radiology, and a manuscript reviewer for IEEE TMI, IEEE TBE, European Radiology, American Journal of Roentgenology (AJR), Academic Radiology, etc. He has served on several national committees of American Association of Physicists in Medicine (AAPM), Radiological Society of North America (RSNA), and American Board of Radiology (ABR), and is the liaison between AAPM and the Society of Cardiac CT (SCCT). Baojun was elected a Fellow of AAPM in 2022. Baojun has authored more than 100 publications and 23 issued patents. He is a frequent lecturer nationally on CT technology.

Board Certification:
American Board of Radiology (Diagnostic Medical Physics)

Research Interests:

Medical Physics
Novel Clinical Applications (Multi-energy CT, Radiomics, PET, SPECT, etc.)
Image Quality and Artifacts
Patient Dosimetry (CT, Interventional, Radiopharmaceutical therapy)


  • University of Iowa, PhD
  • Nanjing University, MS
  • Nanjing University, BS


  • Published on 9/21/2023

    Tivnan P, Kaliaev A, Anderson SW, LeBedis CA, Li B, Andreu-Arasa VC. Utilization of a two-material decomposition from a single-source, dual-energy CT in acute traumatic vertebral fractures. Front Radiol. 2023; 3:1187449. PMID: 37810756.

    Read at: PubMed
  • Published on 5/2/2023

    Li B, Hua N, Li J, Andreu-Arasa VC, LeBedis C, Anderson SW. Quantification of spinal bone marrow fat fraction using three-material decomposition technique on dual-energy CT: A phantom study. Med Phys. 2023 Jul; 50(7):4105-4111. PMID: 37129991.

    Read at: PubMed
  • Published on 5/3/2022

    Abbassi M, Jain A, Shin D, Arasa CA, Li B, Anderson SW, LeBedis CA. Quantification of bone marrow edema using dual-energy CT at fracture sites in trauma. Emerg Radiol. 2022 Aug; 29(4):691-696. PMID: 35503393.

    Read at: PubMed
  • Published on 9/29/2021

    Li B, Hua N, Li J, Andreu-Arasa VC, LeBedis C, Anderson SW. Fat Fraction Measurements Using a Three-Material Decomposition Dual-Energy CT Technique Accounting for Bone Minerals: Evaluation in a Bone Marrow Phantom Using MRI as Reference. AJR Am J Roentgenol. 2022 03; 218(3):553-554. PMID: 34585613.

    Read at: PubMed
  • Published on 9/2/2020

    Li B, Pomerleau M, Gupta A, Soto JA, Anderson SW. Accuracy of Dual-Energy CT Virtual Unenhanced and Material-Specific Images: A Phantom Study. AJR Am J Roentgenol. 2020 11; 215(5):1146-1154. PMID: 32877251.

    Read at: PubMed
  • Published on 9/9/2019

    Oda M, Staziaki PV, Qureshi MM, Andreu-Arasa VC, Li B, Takumi K, Chapman MN, Wang A, Salama AR, Sakai O. Using CT texture analysis to differentiate cystic and cystic-appearing odontogenic lesions. Eur J Radiol. 2019 Nov; 120:108654. PMID: 31539792.

    Read at: PubMed
  • Published on 5/8/2019

    Kawashima Y, Fujita A, Buch K, Li B, Qureshi MM, Chapman MN, Sakai O. Using texture analysis of head CT images to differentiate osteoporosis from normal bone density. Eur J Radiol. 2019 Jul; 116:212-218. PMID: 31153568.

    Read at: PubMed
  • Published on 11/2/2018

    Li J, Qureshi M, Gupta A, Anderson SW, Soto J, Li B. Quantification of Degree of Liver Fibrosis Using Fibrosis Area Fraction Based on Statistical Chi-Square Analysis of Heterogeneity of Liver Tissue Texture on Routine Ultrasound Images. Acad Radiol. 2019 08; 26(8):1001-1007. PMID: 30393055.

    Read at: PubMed
  • Published on 10/27/2018

    Buch K, Kuno H, Qureshi MM, Li B, Sakai O. Quantitative variations in texture analysis features dependent on MRI scanning parameters: A phantom model. J Appl Clin Med Phys. 2018 Nov; 19(6):253-264. PMID: 30369010.

    Read at: PubMed
  • Published on 9/24/2018

    Tsai A, Buch K, Fujita A, Qureshi MM, Kuno H, Chapman MN, Li B, Oda M, Truong MT, Sakai O. Using CT texture analysis to differentiate between nasopharyngeal carcinoma and age-matched adenoid controls. Eur J Radiol. 2018 Nov; 108:208-214. PMID: 30396657.

    Read at: PubMed

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