Sarah Geneser, Ph.D.
Area(s) of Research Focus:
- Inter- and Intra-fraction motion
- Treatment planning optimization
Education and Training
Undergraduate Education: Rice University
Graduate Education: University of Utah
Residency Program: University of California, San Francisco.
D. Raleigh, Z. Seymour, B. Tomlin, P. Theodosopoulous, M. Berger, M. Aghi, S.E. Geneser, D. Krishnamurthy, S. Fogh, P. Sneed, and M. McDermott. Surgical resection and brainbrachytherapy with permanent iodine-125 sources for brain metastasis. Journal of Neurosurgery, 2016.
R. Davidi, Y. Censor, R.W. Schulte, S.E. Geneser, L. Xing. Feasibility-Seeking and Superiorization Algorithms Applied to Inverse Treatment Planning in Radiation Therapy. Contemporary Mathematics, Vol. 636, pp. 83, 2015. B. Fahimian, S.E. Geneser, H. Wu, and L. Xing. Dual-Gated Volumetric Modulated Arc Therapy: A Phantom Feasibility Study. Radiation Oncology, Vol. 9, pp. 209–216, 2014.
T. Kim, L. Zhu, T. Suh, S.E. Geneser, B. Meng and L.Xing. Inverse Planning for IMRT with Nonuniform Beam Profiles Using Total-Variation Regularization (TVR). Medical Image Analysis, Vol. 38, Issue 1, pp. 57–67, 2011. D.J. Swenson, S.E. Geneser, J.G. Stinstra, R.M. Kirby and R.M. MacLeod. Cardiac Position Sensitivity Study in the Electrocardiographic Forward Problem Using Stochastic Collocation and Boundary Element Methods. Annals of Biomedical Engineering, Vol. 39, Issue 12, pp. 2900–2910, 2011.
S.E. Geneser, J.D. Hinkle, R.M. Kirby, B. Wang, B. Salter and S. Joshi. Quantifying Variability in Radiation Dose Due to Respiratory-Induced Tumor Motion. Medical Image Analysis, Vol. 15, Issue 4, pp. 640-649, 2011.
S.E. Geneser, R.M. Kirby, B. Wang, B. Salter and S. Joshi. Incorporating Patient Breathing Variations into a Stochastic Model of Dose Deposition for Stereotactic Body Radiation Therapy. 21st International Conference on Information Processing in Medical Imaging (IPMI), Virginia, Lecture Notes in Computer Science (LNCS) 5636, pp. 688–700, 2009.
S.E. Geneser, R.M. Kirby, and R.S. MacLeod. Application of Stochastic Finite Element Methods to Study the Sensitivity of ECG Forward Modeling to Organ Conductivity. IEEE Transactions on Biomedical Engineering, Vol. 55, Issue 1, pp. 31–40, 2008.
S.E. Geneser, R.M. Kirby, D.B. Xiu and F.B. Sachse. Stochastic Markovian Modeling of Electrophysiology of Ion Channels: Reconstruction of Standard Deviations in Macroscopic Currents. Journal of Theoretical Biology. Vol. 245, Issue 4, pp. 627–637, 2007.
S.E. Geneser, S. Choe, R.M. Kirby, and R.S. MacLeod. The Influence of Stochastic Organ Conductivity in 2D ECG Forward Modeling: A Stochastic Finite Element Study. Proceedings of the 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE Press, pp. 5528–5531, 2005.
S.E. Geneser, R.M. Kirby, and F. B. Sachse. Sensitivity Analysis of Cardiac Electrophysiological Models Using Polynomial Chaos, Proceedings of the 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE Press, pp. 4042–4045, 2005.
S.E. Geneser, S. Choe, R.M. Kirby, and R.S. MacLeod. 2D Stochastic Finite Element Study of the Influence of Organ Conductivity in ECG Forward Modeling. Proceedings of the Joint Meeting of the 5th International Conference on Bioelectromagnetism and 5th International Symposium on Noninvasive Functional Source Imaging within the Human Brain and Heart (BEM&NFSI),Vol. 7, pp. 321–324, 2005.