The following lists most of the projects, research or otherwise, that I've worked on. For a more consise list of my research you can see my list of publications. I am fortunate to work with exceptional collaborators Ramesh Sridharan, Mert Sabuncu, Kayhan Batmanghelich, Ehud Schmidt, Natalia Rost, Manolis Kellis and Jonathan Rosand. I've also been very lucky to work in bioinformatics with professor Michael Brudno and in geophysics with professor Jerry Mitrovica at the University of Toronto.
I'm interested in the prediction of an entire medical image (e.g. MRI) given a subject's genotype and environmental factors. Towards this end, we are currently developing predictive mathematical models, the first of which will be presented at MICCAI 2015 in Munich.
- A.V. Dalca, R. Sridharan, M.R. Sabuncu, P. Golland.
Predictive Modeling of Anatomy with Genetic and Clinical Data.
In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS 9351, pp. 519�526, 2015.
- Co-organizing the second MICGen: MICCAI Workshop on Imaging Genetics at MICCAI 2014 after a very successful inaugural MICGen 2014
- K.N. Batmanghelich, A.V. Dalca, M.R. Sabuncu, P. Golland.
Joint Modeling of Imaging and Genetics,
In Proc. IPMI: International Conference on Information Processing and Medical Imaging, LNCS 79
17, pp. 766–777, 2013.
Stroke is one of the top causes of death and debilitating injury. We are developing models for extracting important phenotypes from medical stroke imaging to aid in prediction, risk assesment and genetic exploration. Stroke is also a main applications of our imaging genetics models mentioned above.
- A.V. Dalca, R. Sridharan, L. Cloonan, K. M. Fitzpatrick, A. Kanakis, K.L. Furie, J.Rosand, O.Wu, M.Sabuncu, N.S. Rost, P.Golland. Segmentation of Cerebrovascular Pathologies in Stroke Patients with Spatial and Shape Priors. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014.
- Abstract at MICGen 2014.
- R. Sridharan‡, A.V. Dalca‡, K.M. Fitzpatrick, L.
Cloonan, A. Kanakis, O. Wu, K.L. Furie, J. Rosand,
N.S. Rost, P. Golland.
Quantification and Analysis of Large Multimodal Clinical Image Studies:
Application to Stroke. In Proc. MICCAI International Workshop
on Multimodal Brain Image Analysis (MBIA), pp. 18–30, 2013.
‡ equal contribution
tipiX is a new approach for fast and effective visualization of large image collections. This applies to both natural images as well as medical volumes in population studies. The key insight is to collapse inherently high-dimensional imaging data onto an interactive two-dimensional canvas native to a computer screen in a way that enables intuitive browsing of the image data. Several examples will get you started in various domains. The code is available on github.
- A.V. Dalca, R. Sridharan, N.S. Rost, P. Golland.
tipiX: Rapid Visualization of
Large Image Collections In MICCAI-IMIC Interactive Medical Image Computing Workshop, 2014.
Best paper award for impact and usability.
Finalist CSAIL Amazing Research Highlight Competition.
Nerve Bundle Tracking
Mapping of nerve bundles is essential for diagnosis and treatment planning of spinal pathologies, and offers substantial benefits for image-guided interventions. Manual segmentation, however, is quite challenging and time consuming, and automatic segmentation cannot use the traditional methods due to the challenging image and nerve properties. In this work we present a more general representation and particle filter based model for nerve segmentation with minimal input from a radiologist.
Correct predictions of post-glacial sea level change have been instrumental in advancing our understanding of Earth’s internal structure, ice age and modern climate, and human migrations. In this work, we introduced a model for sediment redistribution built on top of a (modified) sea-level theory, and showed the improvements of the new model in an area with heavy sediments.
With VARiD, an HMM-based model and tool for simultaneously calling genetic variants from multiple platforms, we showed a significant advantage of modelling color-space and (multiple) letter-space reads into one framework.
This was a review examining the algorithms behind rapid recent developments in genome variation with high througput sequencing.
With Marc Fiume, I worked on the statistical part of Stephen Rumble's SHRiMP - the popular read mapping algorithm which could handle both letter-space and color-space technologies simultaneously. SHRiMP has significantly evolved since the original publication.
FRESCO is an alignment algorithm that can align sequences given a wide range of distance functions, allowing sequence alignment with more complex models or very particular settings.
Since 2010, I've taken pictures of the Boston Skyline from a high vantage point. The more than one million images have been captured with different high resolution cameras (SLRs, GoPros, P&S, cell phone cameras). Some pictures are singletons (just one picture was taken for, say, that week or that day) whereas others are part of series or timelapses (and vary from 1/second to 1/minute, etc). I'm happy to share this data and am currently setting up a repository for it
. There are several cool projects that could be done. Go to the project homepage to explore samples from the data with tipiX, and get more information!
SciEx is an initiative started by Zoya Bylinskii and myself to promote excitement in science. We are starting with a video competition where entries will aim to be stimulate interest in science for the younger generation in a way that x-games youtube videos stimulate interest in sports.
A video project with David Gifford and Boston Ballet. We want to capture the movement of the ballet at various time and personal scales, and here present a timelapse with various speeds and angles at practice in A Day of Grace with Boston Ballet.
K12 Video - Machine Learning
MIT+K12 is a project that offers short video tutorials that help educate K-12 students about various science and engineering topics. Together with a few friends we are working on several videos about Machine Learning, Probability and Algorithms. Once they are finished and (hopefully) accepted by the MIT+K12 group, they should be viewable on their website and YouTube.
Project Ideas for Computer Vision
Over time I've gathered several research directions/projects (mostly relevant to computer vision) that I wished I could do myself but realized they don't fit in my schedule. Some are small exercises (a good project course) and others are research directions. Talking to many people, I realized others are in this scenario - i'm working on introducing a site for sharing these ideas so that others might do it.
Together with Michael Rubinstein we launched a DYI balloon up to the lower atmosphere and retreived video from two GoPro hero 2, accelerometer and and GPS data.