Dr. Ulas Bagci,
2017/September Our kidney and cortex segmentation work appears in Medical Image Analysis Journal
Center for Research in Computer Vision (CRCV), UCF.
2017/Aug Harish's work is nominated for BCI 2017 award: Gold Standard for epilepsy/tumor surgery coupled with deep learning offers independence to a promising functional mapping modality
2017/Aug Our deep learning based retinal fluid detection and quantification paper is accepted to MICCAI-RETOUCH Challenge
2017/July MICCAI-Multimodality Whole Heart Segmentation paper is accepted for publication
2017/July Aliasghar was enlisted as one of the AHA CVRI Young investigator award finalists for his deep learning based Cardiovascular MRI analysis work.
2017/July RSNA 2017 abstract is accepted as podium presnetation:
Title: Deep Learning for Cardiac MRI: Automatically Segmenting Left Atrium Expert Human Level Performance
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Prof. Bagci is a faculty member at the Center for Research in Computer Vision (CRCV), and the Assistant Professor in University of Central Florida (UCF). His research interests are image processing and statistical machine learning and their applications in biomedical and clinical imaging. Previously, Prof. Bagci was a staff scientist and the lab manager at the NIH's Center for Infectious Disease Imaging (CIDI) Lab, department of Radiology and Imaging Sciences (RAD&IS). At NIH, Prof. Bagci has developed and implemented educational and scientific research initiatives, and mentored postdoctoral and postbaccalaureate fellows for quantitative image analysis in clinical and pre-clinical projects at the Clinical Center. Prof. Bagci had been the leading scientist (image analyst) in biosafety/bioterrorism project initiated jointly by NIAID and IRF. He obtained his PhD degree from School of Computer Science, University of Nottingham (UK) in collaboration with Radiology department of University of Pennsylvania (with Prof. Udupa, MIPG). He has masters from Electrical Engineering and Computer Sciences and certificates of mastery from statistics, public health, and clinical trials fields. Prof. Bagci is senior member of IEEE and RSNA, and member of scientific organizations such as Society of Nuclear Medicine and Molecular Imaging (SNMMI), American Statistical Association (ASA), Royal Statistical Society (RSS), AAAS, and MICCAI. Prof. Bagci has served as a program committee member for various conferences, and a ad-hoc reviewer for many prestigious journals in his fields and received best reviewer awards (most recently MICCAI 2016 Best Scientific Reviewer Award). Prof. Bagci is the recipient of many awards including NIH’s FARE award (twice), RSNA Merit Certificates (3 times), best paper award, poster prize, and highlights in journal covers, media, and news. Prof. Bagci will be co-chair of Image Processing Track of SPIE Medical Imaging Conference, 2017.
- 2014-Now, Assistant Prof., Center for Research in Computer Vision, University of Central Florida, FL, USA.
- 2013-2014, Staff Scientist (Title42g) and Lab Manager, Center for Infectious Disase Imaging, NIH, MD, USA.
- 2012-2013, Lab Manager and Senior Research Fellow, Center for Infectious Disase Imaging, NIH, MD, USA.
- 2010-2012, ISTP Research Fellow, Radiology and Imaging Sciences, National Institutes of Health (NIH), MD, USA.
- 2009, Visiting Research Fellow, University of Pennsylvania, PA, USA.
- 2006-2009, Marie Curie Research Fellow, University of Nottingham, UK.
My research interests focus on two aspects. First, I have been developing effective and high-throughput scientific methods in the following majors:
- 2010, PhD. Computer Science, University of Nottingham (UK). In Collabroation with MIPG of University of Pennsylvania.
- 2005, MSc. Electrical Engineering and Computer Sciences, Koc University, Turkey.
- 2003, BSc. Electrical and Electronics Engineering, Bilkent University, Turkey.
Second, I have been using these techniques to address challenging problems in computational radiology and biomedical engineering applications. My expertise include the following keywords:
- Medical Image Processing/Analysis,
- Statistical Machine Learning,
- Imaging Modalities: MRI, PET, CT, PET/CT, fMRI, PET/MRI, Histology,
- Computer Vision and Image Processing: Image Segmentation, Image Registration, Shape Analysis, Object Tracking, Image Quantification, Image Enhancement, Object Tracking, Object Recognition, Multi-Organ recognition and segmentation, joint segmentation of multiple images, Gabor wavelets,
- Pattern Recognition: Deep learning, Multi-task learning, Graph Sparsification, Support vector machines, neural networks, Computer aided diagnosis methods, feature extraction, boosting, probabilistic boosting tree, random forest, graph cut, random walk, graph search, probabilistic graphical models, radiomics, feature extraction and dimension reduction, linear discriminant analysis, principal component analysis,
- Clinical and pre-clinical applications: Cardiac Imaging, Abdominal Imaging, Obesity and Metabolic Research, Pulmonary Imaging, Infectious lung disease, lung cancer, pancreas cancer, kidney cancer, liver cancer, nuclear medicine imaging, radiology, fibrosis, breast cancer, pre-clinical imaging, fat quantification, brown fat identification, prostate cancer imaging and analysis.
- 2016 Best Scientific Reviewer Award, MICCAI 2016.
- 2015 Recognized Reviewer for Distinguished Service at IEEE ISBI 2015.
- 2014 Selected as Distinguished Reviewer by Elsevier.
- 2014 RSNA Certificate of Merit: The State-of-the-Art and Recent Advances in Pulmonary Image Analysis Techniques.
- 2014 RSNA Certificate of Merit: Computerized Detection and Classification of Pulmonary Pathologies from CT Images: Current Approaches, Challenges, and Future Trends.
- 2014 Novel PET Image Segmentation/Quantification study is highlighted in the cover of IEEE Transactions on Biomedical Engineering Journal.
- 2014 Winner of the Fellows Award for Research Excellence (FARE) Award by NIH (supervised Dr Xu).
- 2013 Winner of the Fellows Award for Research Excellence (FARE) Award by NIH.
- 2013 Highlighted in MDLinx due to the first MRI-PET, PET-CT, and MRI-PET-CT co-segmentation software.
- 2013 Highlighted in AuntMinnie due to the first MRI-PET, PET-CT, and MRI-PET-CT co-segmentation software.
- 2012 Best Poster Prize (Molecular Imaging of Infectious Diseases, corresponding-author).
- 2012 Winner of the Fellows Award for Research Excellence (FARE) Award by NIH.
- 2011 RSNA Education Exhibit Merit Award (co-author).
- 2010-2012 NIH Imaging Sciences Training Program (ISTP) Fellowship.
- 2006-2009 Marie Curie Research Fellowship, Fp6 Marie Curie Action Programme.
- 2006 IEEE Best Student Paper Award-IEEE Conference on Signal Processing and Communications Applications.
- Developing Next Generation Image Analysis Methods for Infectious Diseases.Imaging of Infection and Inflammation" track of the World Molecular Imaging Congress (WMIC), NYC, NY.
- Advances in Lesion Quantification from PET/CT and PET/MRI.SIAM-Imaging Science conference, Albuquerque, New Mexico.
- Automatic Quantification of Whole Body Adiposity.Soochow University, Suzhou, China.
- The Role of Imaging and Image Analysis in Public Threating Diseases.Soochow University, Suzhou, China.
- Quantitative PET Image Analysis: Applications in Cancer and Infectious Diseases.Moffitt Cancer Center, Tampa, FL, USA.
- Recent Advances in Clinical Image Processing: Quantification of PET/CT and PET/MR Images. Center for Medical Image Computing, University of College London (UCL), London, United Kingdom.
- Fuzzy Connectedness Image Co-Segmentation for Hybrid PET/MRI and PET/CT Scans. Computational Methods for Molecular Imaging Workshop-MICCAI, Boston, MA, USA.
- Advanced Methods for Quantification of PET, PET/CT, and MRI/PET Images. Department of Computer Engineering, University of Central Florida, Orlando, FL, USA.
- Advanced Methods for Quantification of PET, PET/CT, and MRI/PET Images. MIPG Seminar Series, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
- Advanced Methods in Pulmonary Image Analysis: Applications in Infectious Lung Diseases. Brown Bag Lecture Series, National Library of Medicine (NLM), Bethesda, MD, USA.
- Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images. NIAID Integrated Research Facility (IRF), Fort Detrick, Frederick,, MD, USA.
- Computational Radiology Approaches for Quantifying Pulmonary Infections in Small Animal Images. The third Annual Seminar on Molecular Imaging of Infectious Diseases, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
- Hierarchical Scale Based Multi-Object Recognition of 3D Anatomical Structures. MIPG, Department of Radiology, University of Pennsylvania, PA, USA.
- Clinical Image Processing and Analysis - Automated methods for detection, recognition, and segmentation of anatomical and functional objects. National Cancer Institute-Fredrick, SAIC, Frederick, MD.
- Hierarchical Scale Based Multi-Object Recognition of 3D Anatomical Structures. Imaging Biomarkers and Clinical Image Processing Group, NIH, USA.
- Automatic Detection of Tree-in-Bud Patterns from CT scans. Clinical Image Processing Group, NIH, USA.
- Automatic Best Reference Slice Selection for 3D Volume Reconstruction from 2D Histological Slices. Computational Bio-medicine Lab, University of Houston, USA.
- Localisation of Abdominal Organs for Medical Image Analysis. Computational Bio-medicine Lab, University of Houston, USA.
- Oriented Model Based Localisation of Abdominal Organs in Medical Images.Marie Curie Workshop, on Medical Image Analysis, University of Nottingham, UK.
- Automatic Best Reference Slice Selection for 3D Volume Reconstruction of a Mouse Brain From Histological Sections.MIPG, University of Pennsylvania, PA.
- The Role of Intensity Standardization in Medical Image Registration.Port d'Informacio Cientifica (PIC), Universitat Autonoma de Barcelona (UAB), Barcelona, Spain.
- Registration of Standardized Histological Images in Feature Space for 3D Volume Reconstruction.Academic Radiology, Queen's Medical Centre, Nottingham, UK.
- Multi-resolution Elastic Image Registration in Standard Intensity Scale.Marie Curie Workshop on Medical Image Analysis, Nottingham, UK.
- Dual-Tree Complex Wavelet Transform.CMIAG, University of Nottingham, UK.
- Brain Image Warping.CMIAG, University of Nottingham, UK.
- Brain Image Analysis in Alzheimer's Disease.CMIAG, University of Nottingham, UK.
- MATLAB tutorial for machine learning applications.Koc University,Istanbul, Turkey.
- Musical Genre Classification.SIGNALIST, Istanbul Technical University, Istanbul, Turkey..
- IEEE Transactions on Medical Imaging
- IEEE Transactions on Biomedical Engineering
- IEEE Transactions on Image Processing
- IEEE Transactions on Neural Networks and Learning Systems
- IEEE Transactions on Computational Biology and Bioinformatics
- IEEE Transactions on Information Forensics and Security
- IEEE Journal of Biomedical and Health Informatics
- IEEE Signal Processing Letters
- Medical Image Analysis (Elsevier)
- Computer Vision and Image Understanding (Elsevier)
- Computers in Biology and Medicine (Elsevier)
- Computerized Medical Imaging and Graphics (Elsevier)
- Pattern Recognition Letters (Elsevier)
- Artificial Intelligence in Medicine (Elsevier)
- Neurocomputing (Elsevier)
- Intern. Journal of Computer Assisted Tomography
- Plos One
- Radiographics (RSNA)
- Medical Physics (RSNA)
- ACM Communications
- Machine Vision and Applications
- Clinical Case Reports
- Nature Scientific Reports
- Nature Methods
- Nature Medicine
- Sarfaraz Hussein (Ph.D. student, UCF)
- Harish Raviprakash (Ph.D. student, UCF)
- Naji Khosrovan (Ph.D. student, UCF)
- AliAsghar Mortazi (Ph.D. student, UCF)
- Neslisah Torosdagli (Ph.D. student, UCF)
- Ismail Irmakci (Ph.D. student, Ege University)
- Nandakishore Puttashamachar (MSc. student, UCF)
- Arjun Watane (Undergraduate student, UCF)
- Ziyue Xu (PostDoc), Now Staff Scientist at NIH.
- Awais Mansoor (PostDoc), Now PostDoc at Children's Hospital, DC.
- Mingchen Gao (PostDoc), Now contnue her PostDoc fellowship at NIH.
- Poay Hoon Lim (Ph.D. student), Now PostDoc at University of Montreal, Canada.
- Kirsten Jaster-Miller (Post-Bac student), Now MedSchool Student at Case Western Reserce/Cleveland Clinics.
- Brent Foster (Post-Bac student), Now Ph.D. Student at University of California at Davis.
- Mario Buty (Post-Bac studet), Now continue his fellowship at NIH.
- Aaron Wu (Post-Bac studet), Now continue his fellowship at NIH.
- Neil Mendhiratta (Intern, NIH), Now continue his studentship at NYY School of Medicine.
- RSS (Royal Statistical Society) Member
- ASA (American statistical associations) Member
- IEEE Senior Member
- IEEE Signal Processing Society Member
- IEEE Engineering in Medicine and Biology Society Member
- AAAS Member
- MICCAI Member
- SNMMI Member
- RSNA (Radiological Society of North America) Associate Member
- Editorial Board Member of Computers in Biology and Medicine Journal (Elsevier)
- Editorial Board Member of World Journal of Radiology
- Program Committee Member, Computational Methods and Clinical Applications in Spine Imaging, Workshop, MICCAI 2013.
- Program Committee Member, Computational Methods and Clinical Applications in Spine Imaging, Workshop, MICCAI 2014.
- Program Committee Member, Computational Methods and Clinical Applications in Spine Imaging, Workshop, MICCAI 2015.
- Program Committee Member, Opthalmic Medical Image Analysis, Workshop, MICCAI 2014.
- Program Committee Member, Computational Methods for Molecular Imaging (CMMMI), Workshop, MICCAI 2014.
- Program Committee Member, Computational Methods for Molecular Imaging (CMMMI), Workshop, MICCAI 2015.
- Program Committee Member, SPIE Medical Imaging, 2017.
- Chair, SPIE Medical Imaging-Image Processing Track, 2017.
| Mailing address:
Dr. Ulas Bagci
Center for Research in Computer Vision (CRCV)
4328 Scorpius Street, HEC 221, UCF
Orlando, Florida 32816, USA.
Last updated September, 2015 by Ulas Bagci.