MICCAI 2015


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Oct. 9th (Final Schedule)

8:30 AM – 8:40 AM: Opening remarks

8:40 AM – 9:30 AM: Keynote Talk by Dr. May Dongmei Wang, Ph. D., Associate Professor, The Wallace H. Coulter Joint Department of Biomedical Engineering Kavli Fellow, Georgia Research Alliance Distinguished Cancer Scholar, Fellow of AIMBE, Georgia Institute of Technology and Emory University

Abstract:

Rapid advancements in biotechnologies such as omic (genomics, proteomics, metabolomics, lipidomics etc.), next generation sequencing, bio-nanotechnologies, molecular imaging, and mobile sensors etc. accelerate the data explosion in biomedicine and health wellness. Multiple nations around the world have been seeking novel effective ways to make sense of "big data" for evidence-based, outcome-driven, and affordable 5P (Patient-centric, Predictive, Preventive, Personalized, and Precise) healthcare. We conduct multi-modal and multi-scale (i.e. molecular, cellular, whole body, individual, and population) biomedical data analytics research for discovery, development, and delivery including histopathology imaging informatics. Pathology is one of the corner stone in modern clinical diagnosis. But it heavily depends on pathologists' memorization of biomarker and tissue imaging morphology and leads to variations in diagnosis. To shift from empirical-training-based to evidence-based precision medicine, data-driven objective assessment has been proposed for several decades to assist clinical decision making. With rapid advancement of biotechnology, more biomarker imaging modalities are available with increased spatial, temporal and intensity resolutions (e.g. multiplex quantum dot imaging, imaging mass spectrometry etc.). Also, as EHR gets more widely adopted, biomedical imaging informatics is taking off as one of fast growing disciplines. In this talk, first, I will highlight major challenges in biomedical imaging informatics pipeline consisting of data quality control, information feature extraction, advanced knowledge modeling, decision making, and proper action taking through feedback. Second, I will present informatics methodological research in data integrity and integration, and semi-automatic imaging data analytics for clinical decision support. I will show examples such as (i) Q-IHC that quantifies multiplexing in vitro diagnostic QD imaging data; (ii) TissueWiki that archives and analyzes multi-terabytes of raw and meta-information from Immunohistochemistry (IHC), Human Protein Atlas (HPA); tissue imaging mass spectrometry (IMS) data from Georgia Tech's Center of Imaging Mass Spectrometry; and high resolution multiplexed Quantum Dots (QD) imaging data from Emory-Georgia Tech Cancer Nanotechnology Center et al. Our research has been supported by NIH, NSF, Georgia Research Alliance, Georgia Cancer Coalition, Emory-Georgia Tech Cancer Nanotechnology Center, Children's Health Care of Atlanta, Atlanta Clinical and Translational Science Institute, and industrial partners such as Microsoft Research and HP.

Biography:

Dr. May Dongmei Wang is an Associate Professor in the Joint Department of Biomedical Engineering of Georgia Tech and Emory and School of Electrical and Computer Engineering of Georgia Tech. She is a Kavli Fellow, a Georgia Research Alliance Distinguished Cancer Scholar, and a Fellow of The American Institute for Biological and Medical Engineering (AIMBE). She serves as Co-Director of Biomedical Informatics Program of Georgia Tech in Atlanta Clinical and Translational Science Institute (ACTSI), Co-Director of Georgia-Tech Center of Bio-Imaging Mass Spectrometry, and Biocomputing and Bioinformatics Core Director in Emory-Georgia-Tech Cancer Nanotechnology Center. She is also with Emory Winship Institute, Georgia Tech IBB and and IPaT. Prof. Wang’s research is in Biomedical Big Data analytics. She focuses on Biomedical and Health Informatics (BHI) for Personalized and Predictive Health such as high throughput NGS and -omic data mining to identify clinical biomarkers, bionanoinformatics, pathological imaging informatics to assist clinical diagnosis, critical and chronic care health informatics for evidence-based decision making, and predictive systems modeling to improve health outcome. Prof. Wang published 190+ peer-reviewed articles in BHI. She is the corresponding/co-corresponding author for articles published in Journal of American Medical Informatics Association (JAMIA), Journal of Biomedical and Health Informatics (JBHI), IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Proceedings of The IEEE, IEEE Transactions on Information Technology in Biomedicine (TITB), Proceedings of National Academy of Sciences (PNAS), Annual Review of Medicine, Nature Protocols, Circulation Genetics, Nanomedicine, Annals of BME (ABME), and Trends in Biotechnology etc. She has led RNA-data analysis investigation within FDA-led Sequencing Consortium (SEQC) of MAQC-III. Currently, Prof. Wang serves as the Senior Editor for IEEE Journal of Biomedical and Health Informatics (J-BHI), an Associate Editor for IEEE Transactions on Biomedical Engineering (TBME), and an Emerging Area Editor for Proceedings of National Academy of Science (PNAS). She also serves as IEEE EMBS Biomedical and Health Informatics Technical Committee Chair. She is an IEEE-EMBS 2014-2015 Distinguished Lecturer, and an EMBS Administrative Committee Officer representing North America. In addition, Dr. Wang has devoted to the training of young generation of data scientists and engineers, and is a recipient of Georgia-Tech’s Outstanding Faculty Mentor for Undergraduate Research.

9:30 AM – 9:45 AM: Skeletal Muscle Cell Segmentation Using Distributed Convolutional Neural Network
Manish Sapkota, Fuyong Xing, Fujun Liu, and Lin Yang

9:45 AM – 10:00 AM: High Performance Analysis of Compressed Dynamic CT Perfusion Image Data for Acute Care of Ischemic Stroke
Renan Sales Barros, Edwin Bennink, Jorrit Posthuma, Jaap Oosterbroek, Charles Majoie, Hugo de Jong, Silvia Delgado Olabarriaga, and Henk Marquering

10:00 AM – 10:15 AM: Nuclei Detection Ensemble Workflows Across Clustered Infrastructure
Jian Ren, Javier Diaz-Montes, Joel Saltz, Tahsin Kurc, Manish Parashar, David Foran, and Xin Qi

10:15 AM – 10:30 AM: A GPGPU-based Efficient Framework For Microscopic Muscle Images Enhancement
Bing Liu, Xiangfei Kong, Yuanpu Xie, and Lin Yang

10:30 AM – 11:00 AM: Coffee Break

11:00 AM – 11:15 AM: A Study of Database Configurations for Managing and Querying Large Volumes of Image Segmentation Results
Mehak Mehta, Sai Santhosh Vaidam Anandan, Joel Saltz, and Tahsin Kurc

11:15 AM – 11:30 AM: A Framework for The Creation of Ultra-high Resolution 3-dimensional Models of The Human Brain on Massively Parallel Supercomputers
Hartmut Mohlberg, Bastian Tweddell, and Katrin Amunts

11:30 AM – 11:45 AM: High Throughput Automatic Muscle Image Segmentation Using Cloud Computing and Multi-core Programming
Zizhao Zhang, Fuyong Xing, Fujun Liu, and Lin Yang

11:45 AM – 12:00 PM: Characterizing Human Retinotopic Mapping with Conformal Geometry: Conformal Distortion Analysis
Duyan Ta, Jie Shi, Brian Barton, Alyssa Brewer, Zhong-Lin Lu, and Yalin Wang

12:00 PM – 12:15 PM: Enabling Large-scale Image Analysis Workflows on Federated High-performance Resources
Daihou Wang, Manish Parashar, David J. Foran, and Xin Qi

12:15 PM – 12:20 PM: Closing remarks