"Relating Retinal Anatomy, Pathology, Function, and Therapy Guidance: Analysis of Ophthalmic 3D OCT"
Tuesday, Oct. 7 4 p.m. Hodson Hall 110 Auditorium, Homewood campus Reception to follow
Abstract: Accurate and reliable image segmentation is of great importance in quantitative medical image analysis. In ophthalmology, translational applications of medical imaging were —until recently —limited to 2D analyses of fundus photographs. With a fast-growing routine clinical use of 3D imaging modalities like optical coherence tomography (OCT), ophthalmologists (same as radiologists decades ago) are faced with ever-increasing amounts of image data to analyze. Quantitative outcomes of such analyses are growing in importance. Yet, daily interpretation of clinical ophthalmic OCT images is still typically performed visually and qualitatively, with quantitative clinical analysis being an exception rather than the norm. Since performing full OCT image segmentations in 3D is not feasible for a physician in clinical setting due to the time constraints, quantitative and highly automated analysis methods must be developed. Our approach to simultaneous segmentation of multiple interacting surfaces appearing in the context of other interacting objects will be presented. The reported methods are part of the family of graph-based image segmentation methods dubbed LOGISMOS for Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces. This family of methods guarantees solution optimality with direct applicability to n-D problems. The talk will present new methods and approaches developed during our ongoing ophthalmic OCT image analysis projects, including morphologic analyses of normal and pathologic retinal OCT, determination of structure—function relationships in glaucoma, methods for image-guided treatment of age-related macular degeneration, and approaches applicable to other vision impairing and/or blinding diseases.
Bio: Milan Sonka received his PhD degree in 1983 from the Czech Technical University in Prague. He is associate dean for Graduate Programs and Research of the College of Engineering at the University of Iowa, professor of electrical & computer engineering, professor of ophthalmology & visual sciences, and radiation oncology, director of the Iowa Institute for Biomedical Imaging, IEEE Fellow, and AIMBE Fellow. His research interests include medical imaging and knowledge-based image analysis with emphasis on cardiovascular, pulmonary, orthopedic, cancer, and ophthalmic image analysis. He is the first author of four editions of Image Processing, Analysis and Machine Vision (1993, 1998, 2008, 2014) and co-authored or co-edited 20 books/proceedings. He has published more than 140 journal papers and over 340 other publications, h-index=55. He is editor in chief of the IEEE Transactions on Medical Imaging and a member of the editorial board of Medical Image Analysis. To bring results of his research work to clinical practice, he has co-founded two medical imaging companies—Medical Imaging Applications LLC and VIDA Diagnostics Inc.