Computational Data-based Imaging

Computational Data-based Imaging is a growing field with applications to medical, geophysical and many other disciplines. Numerical methods play an important role in this field, combining robust statistics, numerical linear algebra, numerical optimization and PDE's. The goal of this course is to introduce the students into this inter-disciplinary topic. We will cover (1) an introduction to computational imaging and inverse problem, (2) discretization of some simple PDE's , (3) calculation of sensitivities, (4) from sensitivity to imaging, (5) data uncertainty in imaging, and (6) applications and joint inversion. The course is a hands-on course. We will use different numerical tool and program in Matlab.

REFERENCES

• Computational methods in inverse problems (Vogel)
• Computational methods in geophysical electromagnetics (Haber)
• An introduction to Bayesian Scientific Computing (Somersallo & Calvetti)