Adrian Vasile Dalca

PhD. Candidate, Medical Vision Group
Computer Science and Artificial Intelligence Lab
Electrical Engineering and Computer Science
Massachusetts Institute of Technology

32 Vasser St, 32-D474, Cambridge, MA, 02139. 
adalca at mit dot edu

CV | Resume | Linkedin

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.

Recent 2014:
Papers: stroke segmentation @ MICCAI 2014, mipiX @ MICCAI-IMIC 2014, pipelines @ MICCAI-IMIC 2014
Organizing committee: MICGen workshop @ MICCAI 2014, and MEC challenge @ MICCAI 2014, SciEx
Code: new patch library @ patchlib

Current Main Projects

Joint Modeling of Imaging and Genetics

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.

A Computational Model for Stroke

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.

tipiX - Rapid Visualization of Large Image Collections

tipiX (or mipiX, as it's being renamed) 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. mipiX: 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.

Boston Ballet Timescape

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.

Original design: MiniFolio