Baojun Li, Ph.D., received his Ph.D. from the Univ. of Iowa in 2004 (Advisors: Prof. Joe Reinhardt, Prof. Gary Christensen). His dissertation was on 3D Registration and Warping of Pulmonary CT for Lung Atlas and Radiation Treatment Planning. From 2002 to 2009, he worked at GE Healthcare in the Applied Science Lab as a Senior Scientist, where he was heavily involved in the research and development of Radiographic Tomosynthesis, Low-dose CT, and Dual-energy CT, which led to three commercial products and multiple awards. His current interests include CT clinical protocol optimization, dual-energy CT, and MR/CT/US texture analysis for automatic liver fibrosis staging. Baojun has authored more than 100 publications and 23 issued patents. Baojun currently serves as an Associate Editor for for Medical Physics Journal and OMICS Journal of Radiology, and a reviewer for IEEE Transactions on Medical Imaging, IEEE Transactions on Biomed Eng., Academic Radiology, International Journal of Computer Assisted Radiology and Surgery, Journal of Applied Clinical Medical Physics, Physica Medica, Journal of X-ray Science and Technology, Computational and Mathematical Methods in Medicine. He is an active member of American Association of Physicists in Medicine (AAPM) and Radiological Society of North America (RSNA), having served on several committees and task groups.
American Board of Radiology
- University of Iowa, PhD
- Nanjing University, MS
- Nanjing University, BS
- 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.
- 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. 2018 Nov 02. PMID: 30393055.
- 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.
- 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.
- Published on 10/1/2017
Yu H, Scalera J, Khalid M, Touret AS, Bloch N, Li B, Qureshi MM, Soto JA, Anderson SW. Texture analysis as a radiomic marker for differentiating renal tumors. Abdom Radiol (NY). 2017 Oct; 42(10):2470-2478. PMID: 28421244.
- Published on 11/14/2016
Li B, Jara H, Yu H, O'Brien M, Soto J, Anderson SW. Enhanced Laws textures: A potential MRI surrogate marker of hepatic fibrosis in a murine model. Magn Reson Imaging. 2017 Apr; 37:33-40. PMID: 27856399.
- Published on 10/3/2016
Chang KJ, Collins S, Li B, Mayo-Smith WW. Optimizing CT technique to reduce radiation dose: effect of changes in kVp, iterative reconstruction, and noise index on dose and noise in a human cadaver. Radiol Phys Technol. 2017 Jun; 10(2):180-188. PMID: 27699635.
- Published on 6/1/2016
Yu H, Touret AS, Li B, O'Brien M, Qureshi MM, Soto JA, Jara H, Anderson SW. Application of texture analysis on parametric T1 and T2 maps for detection of hepatic fibrosis. J Magn Reson Imaging. 2017 Jan; 45(1):250-259. PMID: 27249625.
- Published on 6/1/2016
Li B. TU-AB-207A-00: CT Systems Course. Med Phys. 2016 Jun; 43(6):3739-3740. PMID: 28048020.
- Published on 1/1/2016
Fujita A, Buch K, Li B, Kawashima Y, Qureshi MM, Sakai O. Difference Between HPV-Positive and HPV-Negative Non-Oropharyngeal Head and Neck Cancer: Texture Analysis Features on CT. J Comput Assist Tomogr. 2016 Jan-Feb; 40(1):43-7. PMID: 26466116.
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