Radiomics, Big Data and Cloud Computing
Speaker:Prof. Dmitry Goldgof
Department of Computer Science and Engineering
University of South Florida, USA
Date & Time:14 Oct 2015 (Wednesday) 16:00 - 17:00
Organized by:Faculty of Science and Technology


"Radiomics" refers to the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images obtained with CT, PET or MRI. Importantly, these data are designed to be extracted from standard-of-care images, leading to a very large potential subject pool. Radiomics data are in a mineable form that can be used to build descriptive and predictive models relating image features to phenotypes or gene–protein signatures. The core hypothesis of Radiomics is that these models, which can include biological or medical data, can provide valuable diagnostic, prognostic or predictive information. One Radiomics challenges is the need to curate and store large sets image volumes from large number of clinical sites. One such effort in Big Data is NCI supported, The Cancer Imaging Archive (TCIA), which houses a large number of image collections and is used worldwide for cancer research, algorithm development and challenges. Challenges are an increasingly popular approach to engage the research community to advance science forward through collaboration, crowd-sourcing and rigorous evaluation. Cloud Computing is a modern paradigm utilized to reduce the barrier to entry for cancer scientists to participate in challenges. The Cloud-based Image Biomarker Optimization Platform (C-BIBOP) is an open-source platform being built to support algorithm comparison and benchmarking with “live at all times” (not just at conferences) operation paradigm. The talk will introduce concept of radiomics and discuss progress of C-BIBOP implementation.


Dmitry B. Goldgof is an educator and scientist working in the area of biomedical image analysis, video processing, pattern recognition and bioengineering. He is currently Professor in the Department of Computer Science and Engineering at the University of South Florida in Tampa. Dr. Goldgof has graduated 24 Ph.D. and 43 MS students, published over 85 journal and 200 conference papers, 20 books chapters and edited 5 books (citations impact: h-index 42, g-index 78). Professor Goldgof is a Fellow of IEEE and a Fellow of IAPR. He was recently elected to the Board of Governors of IEEE Systems, Man and Cybernetics Society and currently serving on the IEEE Press Editorial Board. Dr. Goldgof is an Associate Editor for IEEE Transactions on Systems, Man and Cybernetics and for International Journal of Pattern Recognition and Artificial Intelligence.