Computational and Analytical Aspects of Image Reconstruction
(July 1317, 2015)
The mathematical study of image reconstruction problems can have a huge impact on human life. More efficient mathematical algorithms for Xray tomography and more accurate mathematical models in seismic or hybrid imaging can lead to better imaging devices in fields such as medicine and remote sensing. Developing the underlying mathematics, including the analysis of reconstruction stability, regularization, singularity characterization, and efficient algorithms, may lead to fewer false positives in fields such as medical, seismic and radar imaging.
This topical workshop will bring together international experts working in computational and analytical aspects of image reconstruction (including but not limited to electronmicroscope tomography, hybrid imaging, radar and sonar, full waveform inversion of seismic imaging and Xray CT) as well as postdoctoral fellows and graduate students. There will be multiple introductorylevel talks for earlycareer researchers and nonspecialists in the area on both the mathematics involved and the scientific and industrial applications. Speakers and participants from industry will be included to strengthen the practical aspects of the workshop.
Application review will begin on March 9, 2015.
Organizing Committee
 Gaik Ambartsoumian
(University of Texas at Arlington)  Vladimir Druskin
(SchlumbergerDoll)  Esther Klann
(Johannes Kepler University)  Venkateswaran P. Krishnan
(TIFR Centre for Applicable Mathematics)  Alfred Louis
(Universität des Saarlandes)  Eric Todd Quinto
(Tufts University)
Output of iterations of a MumfordShah level setbased method for simultaneous reconstruction and segmentation of a torso phantom from noisy CT data. Images courtesy of Esther Klann relating to work in E. Klann, R. Ramlau, and W. Ring, Inverse Problems and Imaging, Vol. 5 (2011), 137166.


