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.

SCI Publications

2000


T. Tasdizen, J.-P. Tarel, D.B. Cooper. “Improving the Stability of Algebraic Curves for Applications,” In IEEE Transactions on Image Processing, Vol. 9, No. 3, pp. 405--416. March, 2000.



T. Tasdizen, D.B. Cooper. “Boundary Estimation from Intensity/Color Images with Algebraic Curve Models,” In Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, IEEE, 2000.
DOI: 10.1109/icpr.2000.905308

ABSTRACT

A concept and algorithm are presented for non-iterative robust estimation of piecewise smooth curves of maximal edge strength in small image windows-typically 8/spl times/8 to 32/spl times/32. This boundary-estimation algorithm has the nice properties that it uses all the data in the window and thus can find locally weak boundaries embedded in noise or texture and boundaries when there are more than two regions to be segmented in a window; it does not require step edges-but handles ramp edges well. The curve-estimates found are among the level sets of a dth degree polynomial fit to "suitable" weightings of the image gradient vector at each pixel in the image window. Since the polynomial fitting is linear least squares, the computation to this point is very fast. Level sets then chosen to be appropriate boundary curves are those having the highest differences in average gray level in regions to either side. This computation is also fast. The boundary curves and segmented regions found are suitable for all purposes but especially for indexing using algebraic curve invariants in this form.


1999


T. Tasdizen, J.-P. Tarel, D. B. Cooper. “Algebraic curves that work better,” In Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 1999.
DOI: 10.1109/cvpr.1999.784605


1998


T. Tasdizen, L. Akarun, C. Ersoy. “Color Quantization with Genetic Algorithms,” In Signal Processing: Image Communication, Vol. 12, pp. 49--57. 1998.


1997


Z. Lei, T. Tasdizen, D.B. Cooper. “PIMS and Invariant Parts for Shape Recognition,” In Sixth International Conference on Computer Vision, Narosa Publishing House, 1997.
DOI: 10.1109/iccv.1998.710813