Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

3rd International MICCAI Workshop on Spatiotemporal Image
Analysis for Longitudinal and Time-Series Image Data (STIA'14)

MICCAI Workshop Th-W22, Thursday September 18, 2014, Boston


  • Guido Gerig, University of Utah, USA (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • Stanley Durrleman, INRIA, Paris, France (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • Tom Fletcher, University of Utah, USA (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • Marc Niethammer, University of North Carolina at Chapel Hill, USA (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • Xavier Pennec, INRIA Sophia Antipolis, France (This email address is being protected from spambots. You need JavaScript enabled to view it.)

Workshop Proceedings: STIA'14 LNCS Series Springer Verlag


2012 Volume 7570, 2012, DOI: 10.1007/978-3-642-33555-6

Keynote Speaker: Yicong Wu, NIH-NIBIB
Yicong Wu

Toward the construction of a 4D dynamic brain atlas in the C.elegans embryo

Yicong Wu and Hari Shroff
NIBIB Lab: Section on High Resolution Optical Imaging (HROI)

Abstract: The Caenorhabditis elegans embryo with only 302 neurons and ~7000 synapses provides an excellent model to understand how neural circuit assembly occurs in vivo. Direct observation of neurodevelopment during 14 hours of embryogenesis is challenging because conventional 4D microscopy induces too much phototoxicity and late stage embryos move too quickly to be captured with conventional microscopy. We have developed a novel imaging and data processing pipeline that addresses these problems, allows visualization of neurodevelopmental decisions in live embryos, and paves the way to establish a 4D dynamic neurodevelopmental atlas for all the nematode neurons. First, we invented a diSPIM system (dual-view, inverted, selective plane illumination microscope) with an isotropic resolution of 330 nm. This technical advance allowed us to image the nematode embryo in toto with high resolution and speed for the entirety of embryogenesis without detectable phototoxicity. Second, we merged two-color nuclear and neural imaging with automated lineaging techniques to identify cells of interest and visualize their neurodevelopmental dynamics. This enables us to visualize cell migration and neurite outgrowth decisions in the developing nematode brain. Finally, we propose new algorithms to straighten the worm embryos during elongation, segment the neurons/axons, and align cell positions and migration patterns among different embryos. Our final goal is to establish a four dimensional neural wiring map of all the nematode neurons throughout embryogenesis and also after hatching to a larval. 

Biosketch: Dr. Yicong Wu received his Ph.D. in Electronic and Computer Engineering from Hong Kong University of Science and Technology in 2007 under the supervision of Dr. Jianan Qu. He joined Dr. Xingde Li's group as a postdoctoral fellow at the University of Washington, and then moved with the Li group to Johns Hopkins in 2009, where he worked on developing endomicroscopy technologies for nonlinear optical imaging. He is currently a staff scientist in NIBIB's Section on High Resolution Optical Imaging led by Dr. Hari Shroff. His research interest centers on the development of new imaging tools for applications in biological and clinical research.

Rationale STIA:

The proposed workshop aims to be the follow-up of the first and second international workshops on Spatiotemporal Image Analysis (STIA) for Longitudinal and Time-Series Image Data. The first workshop was held in conjunction with MICCAI 2010 in Beijing. The first STIA’10 workshop was a success with 58 full paying attendees in the advanced registrations, 8 podium speakers and 8 poster presentations selected from a total of about 25 submitted papers. Papers were sent from a large variety of institutions from all geographic regions. The 2nd STIA’12 workshop at MICCAI’12 in Nice showed about 70 attendees. As a novelty for STIA, the 13 selected papers (8 oral, 5 posters), reviewed by 25 international experts in this field, were invited to be published in a special Springer Verlag LNCS 7570 proceedings.

The obviously increasing interest of the MICCAI community in a methodology-oriented workshop on longitudinal image data analysis supports, in our view, the organization of a second workshop on the same topic. There seems a clear need for information exchange and brainstorming with respect to this new and rapidly evolving image analysis subdiscipline. Such a workshop focusing more on theoretical and methodological aspects rather than application-driven research would also complement and augment previous workshops dedicated to very specific applications such as “early brain development”. A large numbers of papers have been published in the main journals and conference proceedings over the last two years (for instance, last MICCAI meeting in 2011 had a session dedicated to this topic). The organization of such a workshop on a regular basis would help to establish the MICCAI meetings as a key forum to discuss novel theoretical and methodological advances, to foster collaborations among the specialists in the field, and to provide profound education and information about the state-of-the-art to researchers novel to this topic.

Target Audience:

 There is a rapidly growing interest in the analysis of time-series data. Recent examples are the very successful MICCAI 2008, 2009 and 2011 workshops on image analysis of the early developing brain, where a modeling of brain growth and brain maturation were key topics but with the main focus on a very specific application domain. Our objective is to move beyond such a specific application domain with the proposed workshop by focusing on common underlying methodologies to analyze time-series data. The increased focus on personalized medicine or subject-specific analysis includes processing of time-series data such as pre-/post-therapy or modeling of lesion evolution via parameterized models. Clinical studies of aging, e.g., include series of follow-up scans to stage and model the effect of aging and to determine the onset of accelerated degeneration. Rapidly evolving advanced imaging technology can routinely measure volumetric data in short time intervals, creating 4D datasets that require new, efficient processing, visualization, and quantitative analysis techniques.

The target audience will therefore be researchers interested in or already involved in research and development of methods for studying growth or change patterns in longitudinal and time-series image data. This workshop aims at contributing to a fundamental understanding of data, processing methodology and statistical concepts but also to a review and discussion of existing methods, procedures and problem solutions. We expect to create discussions between researchers, developers and potential users in order to inform about existing technology, image databases for testing and comparison, and to lay the ground for future research.


We are thankful to ICM (Hôpital Pitié Salpêtrière, Brain and Spine Institute, Pariswww and SCI (Scientific Computing and Imaging Institute, Utah ( for sponsoring this workshop.The NA-MIC consortium ( funded by NIH is acknowledged for providing scientific and engineering support.