Sampling (the estimation of the formerly continuous signal from its discrete samples) is an essential part of volume visualization, where datasets are given as a set of points. These points are distributed (due to acquisition and/or data simplification) either regularly or irregularly in space, and therefore studies in sampling theory and data grids bring out many common issues. In this project we seek to research more accurate (and hopefully also more effcient) methods by which to sample and represent discrete signals. Our research extends to issues pertaining to the acquisition of the data as well, via CT, SPECT, MRI, and functional MRI (fMRI).

	VDVR: Verifiable Volume Visualization of Projection-Based Data Z. Zheng, W. Xu, K. Mueller IEEE Transactions on Visualization and Computer Graphics 16(6):1515-1524, 2010
	Applications of optimal sampling lattices for volume acquisition via 3D computed tomography F . Xu and K. Mueller Volume Graphics Symposium Prague, Czech Republic, September 2007 pp. 57-63
	Spline-based gradient filters for high-quality refraction computations in discrete datasets S. Li and K. Mueller Eurographics / IEEE VGTC Symposium on Visualization Leeds, England, June 2005 pp. 217-222
	Methods for effcient, high quality volume resampling in the frequency domain  A. Li and K. Mueller IEEE Visualization 2004 Austin, Texas, October 2004 pp. 3-10
	A frequency-sensitive point hierarchy for images and volumes T. Welsh and K. Mueller IEEE Visualization 2003 Seattle, October, 2003 pp. 425-432
	Space-time points: Splatting in 4D N. Neophytou and K. Mueller Symposium on Volume Visualization and Graphics 2002 Boston, October 2002 pp. 97-106
	Design of accurate and smooth filters for function and derivative reconstruction T. Möller, K. Mueller, Y. Kurzion, R. Machiraju, and R. Yagel 1998 Symposium on Volume Visualization Chapel Hill, October 1998 pp. 143-151
	A comparison of normal estimation schemes T. Möller, R. Machiraju, K. Mueller, and R. Yagel IEEE Visualization'97 Phoenix, October 1997 pp. 19-26
	Evaluation and design of filters using a Taylor series expansion T. Möller, R. Machiraju, K. Mueller, and Roni Yagel IEEE Transactions on Visualization and Computer Graphics vol. 3, no. 2, pp. 184-199, 1997
	Classification and local error estimation of interpolation and derivative filters for volume rendering T. Möller, R. Machiraju, K. Mueller, and Roni Yagel 1996 Symposium on Volume Visualization San Francisco, October 1996 pp. 71-78, 1996.