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Computational Data-based Imaging

Description

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)

People

 

Haber E.

Course director

Verbosio F.

Assistant

Additional information

Semester
Spring
Academic year
2016-2017
ECTS
3
Education
Master of Science in Computational Science, Elective course, Lecture, 1st year

PhD programme of the Faculty of Informatics, Elective course, 1st and 2nd year