Electrical impedance tomography, enclosure method and machine learning
IEEE MLSP 2020, Aalto University, Finland, September 23, 2020. (Talk given online via video stream) PDF (11 MB)
Latest
Invited talk: Electrical impedance tomography, enclosure method and machine learning
Inverse problems seminar, Colorado State University, USA, March 5, 2020. PDF (22 MB)
Invited talk: Classifying stroke from electric boundary data by nonlinear Fourier analysis
Applied mathematics seminar, Rutgers University, USA, February 28, 2020. PDF (14 MB)
Invited talk: Introduction to machine learning
Mathematics seminar, Tokyo University of Science, Japan, January 21, 2020. PDF (14 MB)
Invited talk: Complex principal type operators in the inverse conductivity problem
Inverse problems seminar, The University of Tokyo, Japan, January 22, 2020. PDF (16 MB)
Invited talk: Electrical impedance tomography, enclosure method and machine learning
Mathematics seminar, Tokyo University of Science, Japan, January 21, 2020. PDF (13 MB)
Microcourse on computational inversion
Graduate school in inverse problems,Hiroshima University, Japan, January 15, 2020.
Invited talk: The magic of math: three-dimensional X-ray vision
Applied Mathematics Colloquium,Hiroshima University, Japan, January 15, 2020. PDF (24 MB)
Plenary talk: Inverse Problems and the Nonlinear Fourier Transform
12th Finnish Mathematical Days 2020, Oulu, Finland, January 3, 2020. PDF (22 MB)
What is tomography?
Tomography aims to reveal the internal structure of a patient based on X-ray images taken from different directions. The resulting slice image is formed with a mathematical algorithm.