Math 290J (section 2) current literature in applied mathematics
Mathematical models in image processing and analysis
Organizers: Luminita Vese and Hayden Schaeffer.
Presentations, Time and Location:
Most meetings will be on Fridays, time 12:00-1:00pm, in MS 5233.
Please note that some meetings will be at a different time and location.
All meetings will be announced by email and posted on the class webpage.
Graduate students give presentations from current literature in applied mathematics, image processing, computer vision. Sometimes, we may also have a guest lecturer.
Friday, September 30; Time 12:00pm-1:00pm; Location MS 5233
Melissa Tong: "Rician denoising"
Friday, October 7: Time 12:00pm-1:00pm; Location MS 5233
Joshua Hernandez: "Constant-Variance Resampling of Noisy Images"
Friday, October 14: Time 12:00pm-1:00pm; Location MS 5233
Friday, October 21: Time 12:00pm-1:00pm; Location MS 5233
Yi Yang: "Algorithms for Solving Basis Pursuit Problems."
Friday, October 28: Time 12:00pm-1:00pm; Location MS 5233
Igor Yanovsky (JPL / UCLA): Multilayer Separation using Split Bregman Methods and Applications to Separating Layers of Clouds
Friday, November 4: Time 12:00pm-1:00pm; Location MS 5233
Alejandro Cantarero (UCLA): "Inverse Problems in Elliptic PDEs"
Abstract. In this talk, we will present two methods for the estimation of the parameters and interface location from solution data to embedded interface
elliptic PDEs with piecewise constant coefficients. The first approach is a variational method where we are able to obtain an explicit update
for the coefficients, eliminating the need to solve a non-linear system at each iteration. In the second approach we use the piecewise constant
nature of the coefficients to derive approximate coefficient functions. The interface location and coefficient values can then be recovered by
applying any standard piecewise constant segmentation method. We demonstrate the methods on Poisson's equation and linear elasticity.
Friday, November 11: no meeting
Friday, November 18: Time 12:00pm-1:00pm; Location MS 5233
Ming Yan: "TBA"
Friday, November 25: no meeting
Friday, December 2: Time 12:00pm-1:00pm; Location MS 5233
Yonggang Shi (LONI, UCLA): Intrinsic Methods for Brain Image Analysis
Speaker: Yonggang Shi, Assistant Professor, Lab of Neuro Imaging (LONI),
UCLA School of Medicine
Abstract: In this talk, I will present a suite of novel algorithms and tools
for brain mapping using intrinsic geometry. The key idea in our method is
the use of Laplace-Beltrami eigenfunctions for modeling brain shapes, such
as hippocampus and cortex. These tools have the advantage of being invariant
to pose and scale variances, and robust to deformations from development and
pathology. Using the LB eigenfunctions and topology-preserving evolution, we
have developed a robust approach for surface reconstruction that can remove
outliers while accurately retaining volume information. We also developed
metric optimization methods for highly accurate surface mapping. Combing
these two algorithms, we have a fully automated workflow for the mapping of
hippocampus and other brain structures. Applications these new methods in
the studying of neurological diseases will be demonstrated.