"Advanced Methods for Quantification of PET, PET/CT, and MRI/PET Images"
Dr. Ulas Bagci
National Institutes of Health
Friday, August 22, 2014 · 2:30PM · HEC 101
Magnetic resonance imaging (MRI) and computed tomography (CT) are widely utilized structural imaging modalities. Positron emission tomography (PET),
on the other hand, is a functional imaging modality providing biologic processes at the cellular and molecular level. PET/CT and more recently MRI/PET
scanners provide both structural and functional information jointly, therefore, they are frequently needed by clinicians for diagnosing and characterizing
the disease type accurately. However, all diagnostic measurements require precise segmentation of functional and anatomical images, which is a challenging
task due large variations of pathologies, and difficulty in combining structural and functional information in the same settings.
To address those challenges, in this talk, I will present novel methods for the accurate quantification of lesions from PET, PET/CT and MRI/PET images. The
proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of
regions based on random walk and fuzzy connectedness image co-segmentation. Furthermore, I will also talk about a simple yet effective object/background seed
localization method to make the proposed segmentation process fully automatic. At the end of my talk, I will demonstrate the effectiveness of the proposed
methods both in accuracy and efficiency.
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 computer vision fields. Dr. Bagci began his work at NIH in 2010 when he received an Imaging Science
Training Program (ISTP) Fellowship in 2010-2012. 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. Dr Bagci 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.