I am a graduate student at MIT in the EECS department, advised by Polina Golland. I am interested in models for medical image analysis and the interaction of imaging phenotypes with genetics. I have a side passion for computational photography and vision.
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.
My wife, Monica, is a graduate student at MIT in the Biology department doing exciting research on cancer biology.
We are organizing a workshop on imaging genetics: MICGen 2014. Join us on Sept 14!
We are organizing an education challenge: MEC challenge. Come by our lunch discussion on Sept 15!
See our stroke segmentation work @ main conference [paper] Poster: TP46, Tuesday 3-5pm
See our interactive MIC Workshop papers [tipiX], [pipelines]
Current Main Projects
One of my main interests is on joint modeling of medical imaging and genetic variants. We aim to identify clusters of genetic markers working together to affect brain structure and function, and further explain variances in traits or clinical disease.
- Co-organizing the first MICGen: MICCAI Workshop on Imaging Genetics at MICCAI 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), to appear, 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, To appear 2014.
Current Side Projects
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.
Original design: MiniFolio