JA
Eventhough this course is hard, I love it. Thankyou

In this course you get the chance to get teaching and hands-on experience with the complete workflow of high-resolution tomography analysis. You will get introduced to data acquisition, 3D reconstruction, segmentation and meshing and, finally, 3D modelling of data to extract physical parameters describing mechanical and flow properties. The teaching and the exercises will take place in close interaction with top experts in the field. Exercises will require some basic programming skills, and will be carried out in a common python environment.

JA
Eventhough this course is hard, I love it. Thankyou
YA
Excellent basics on tomography and research oriented course.
JM
Very complete course, it explained the workflow with high precision and good examples. The mathematical background can help you if you want to go deeper in tomography.
AG
Learning lessons are in-depth, explaining various methods in Computed Tomography with real-life examples. Thank you for making this course.
显示:13/13
Excellent basics on tomography and research oriented course.
Eventhough this course is hard, I love it. Thankyou
The framework of theoretical aspects and jupyter notebooks helped me a lot to understand and to create my own pipeline. The FEniCS part of the last week should be given more time, since it is extremely detailed and also relevant.
Awesome course. Very useful in my field of research. I love the modules that covered regularization by total variation. The honours track is the best part! Thanks for such an amazing course.
Very complete course, it explained the workflow with high precision and good examples. The mathematical background can help you if you want to go deeper in tomography.
muy bueno, practico y entendible
Really fantastic course!
The best course
Excellent!
Excellent
Learning lessons are in-depth, explaining various methods in Computed Tomography with real-life examples. Thank you for making this course.
Not a complete course. Lectures are informative but practical examples are limited. Most labs were on single slices but do not discuss combining slices and segmentation processes clearly.
Poor examples