Radiology and Imaging Sciences
Ulas Bagci, PhD
Staff Scientist, Center for Infectious Disease Imaging (CIDI)
Radiology and Imaging Sciences
PhD, University of Nottingham, United Kingdom
MS, Koc University, Turkey
BS, Bilkent University, Turkey
Dr. Bagci is a Staff Scientist in NIH's Center for Infectious Disease Imaging (CIDI) Lab, in Radiology and Imaging Sciences (RAD&IS), where he is conducting research focused on medical image processing, analysis, and scientific visualization fields. Dr. Bagci works closely with Dr. Daniel J. Mollura, MD, Deputy Director of the Center for Infectious Disease Imaging, in development and implementation of CIDI-based educational and scientific research initiatives, in addition to mentoring postdoctoral and postbaccalaureate fellows interested in quantitative image analysis and infectious disease.
Dr. Bagci began his work at NIH in 2010 when he received an Imaging Science Training Program (ISTP) Fellowship in 2010-2012 under the supervision of Dr. Mollura and Dr. David Bluemke. Prior to joining CIDI in 2010, he was a Marie Curie Research Fellow in the Collaborative Medical Image Analysis Group at the University of Nottingham where he was awarded his PhD in April 2010. In 2009, he was a visiting research scholar in the Medical Image Processing Group at the University of Pennsylvania under the supervision of Prof. Jayaram K. Udupa. He received his BSc and MSc degrees in the Electrical and Electronics Engineering Department at Bilkent University, and in Electrical and Computer Engineering from Koc University, Turkey, in 2003 and 2005, respectively. He was the winner of NIH Fellow Award for Research Excellence (FARE) awards in 2012 and 2011.
He has received several awards including Best Poster Prize in Molecular Imaging of Infectious Diseases, RSNA Education exhibit, IEEE - Best Student Paper in the IEEE Conference on SIU, 2006. His recent research interests focus on two aims; (1) development of effective and high-throughput biomedical image analysis, computer vision, pattern recognition, and (2) machine learning techniques for life sciences studies. Dr. Bagci develops and utilizes these techniques to address challenging problems in computational radiology and biomedical engineering. Dr. Bagci is a member of the IEEE, SPIE, RSNA, MICCAI, and BMVA. He is a regular reviewer for IEEE TMI, TBME, TIP, Computerized Medical Imaging and Graphics, Computer Vision and Image Understanding, and Computers in Biology and Medicine. He is also serving as an editorial board member on several journals for image processing and computer vision.
Selected Grants, Honors, and Awards
2013 Winner of Fellows Award for Research Excellence (FARE) Award by NIH
2013 Highlighted in AuntMinnie due to ?rst MRI-PET, PET-CT, and MRI-PET-CT co-segmentation software
2012 Best Poster Prize (Molecular Imaging of Infectious Diseases)
2012 Winner of Fellows Award for Research Excellence (FARE) Award by NIH
2011 RSNA Education Exhibit Merit Award
2010-2012 NIH Imaging Sciences Training Program (ISTP) Fellowship
2006-2009 Marie Curie Research Fellowship, Fp6 Marie Curie Action Program
2006 IEEE Best Student Paper Award-IEEE Conference on Signal Processing and Communications Applications
2005-2006 DPT Grant for Graduate Study in Koc University, Drive-Safe Project
2003-2005 Honored with Vehbi Koc Scholarship, Full Graduate Fellowship, from Koc University
1998-2003 Honored with Full-Scholarship by Bilkent University for BSc Study
1998-2003 Outstanding Student-Scholarship by Turk Telecom
- Joint Segmentation of Functional and Anatomical Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images. U.Bagci, J.K. Udupa, N. Mendhiratta, B. Foster, Z. Xu, J.Yao, X. Chen, D.J. Mollura, Medical Image Analysis, Vol. 17 (8), pp. 929-945, 2013.
- A Computational Pipeline for Quantification of Pulmonary Infections in Small Animal Models Using Serial PET-CT Imaging. U. Bagci, B.Foster, K. Miller-Jaster, B.Luna, B. Dey, WR Bishai, CB Jonsson, S. Jain and DJ Mollura. EJNMMI Res Vol. 3(55), 2013.
- Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images. U.Bagci, J.Yao, K.J.Miller, X.Chen, D.J.Mollura, PlosOne, Vol. 8(2), e57105, 2013.
- Segmentation of PET Images for Computer-Aided Functional Quantification of Tuberculosis in Small Animal Models. IEEE Transactions on Biomedical Engineering, Vol 61(3), pp. 711-724, 2014.
- Introducing Willmore Flow into Level Set Segmentation of Spinal Vertebrae, Poay Hoon Lim*, U.Bagci, and L.Bai, IEEE Transactions on Biomedical Engineering, Vol. 60(1), pp. 115-122, 2013.
- PET Imaging of HER2+ Pulmonary Metastases with 18F-ZHER2:342-Affibody in a Mouse Model; Comparison with 18F-Fluorodeoxyglucose (18F-FDG), Kramer-Marek, G., Bernardo, M., Kiesewetter, D., U. Bagci, Kuban, M., Aras, O., Zielinski, R., Seidel, J., Choyke, P., Capala, J. J Journal Of Nuclear Medicine (JNM),Vol. 53(6), pp. 939-946, 2012.
- A Generic Approach to Pathological Lung Segmentation, Mansoor, A., Bagci, U., Xu, Z., Foster, B., Olivier, K.N., Elinoff, J.M., Suffredini, A.F., Udupa, J.K., Mollura, D.J. IEEE Transactions on Medical Imaging, 2014 (in press).
- Automatic Detection and Quantification of Tree-in-Bud (TIB) Opacities from CT Scans, U.Bagci, J.Yao, A.Wu, J.Caban, T.N. Palmore, A.F. Suffredini, O.A., D.J. Mollura. IEEE Transactions on Biomedical Engineering, Vol 59(6), pp. 1620-1632, 2012.
- Hierarchical Scale-Based Multi-Object Recognition of 3D Anatomical Structures, U.Bagci, X. Chen, J.K.Udupa. IEEE Transactions on Medical Imaging, Vol. 31(3), pp. 777-789, 2012.
- Medical Image Segmentation by Combining Graph Cut and Oriented Active Appearance Models, X.Chen, J.K.Udupa, U.Bagci, Y.Zhuge, J.Yao, IEEE Transactions on Image Processing, Vol. 21(4), pp. 2035-2046, 2012.
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This page last updated on 06/22/2017