Learning Outcomes: The seminar will introduce students to a selected area of the algorithms of computed tomography (CT) reconstruction. The purpose is:
1. to present a review of CT modelling
2. to present the reconstruction algorithms in CT application
3. to find a preference algorithm to solve the corresponding CT problems
Each student will present one selected topic so that they will have the competence to work independently on the selected topic.
Content: In every seminar talk, there is the author/student who writes a 2-4 page summary paper about the subject and gives the talk, and an opponent, whose task is to make questions and stimulate discussion after the presentation. Every student is the author for (at least) one talk and the opponent for another talk. The author/student should send the summary paper to the opponent and to the teachers (email@example.com and firstname.lastname@example.org) on the Thursday preceding the presentation day. The slides should be sent to the teachers latest on the day preceding the presentation. The opponent prepares at least 2-3 questions about the topic to stimulate discussion after the talk. Normal talk is 20-30 minutes.
Assessment Methods and Criteria: searching and reading of literature, writing of summary paper, presentation and preparations, peer review, homework
Workload: 10-12 h contact teaching, 50-60 h independent studies. Attendance in all of part of seminars is compulsory.
1. Kak, Avinash C., Malcolm Slaney, and Ge Wang. "Principles of computerized tomographic imaging." Medical Physics1 (2002): 107-107.
2. Mueller, Jennifer L., and Samuli Siltanen. Linear and nonlinear inverse problems with practical applications. 10. Siam, 2012.
3. The alternating direction method of multipliers (ADMM) https://stanford.edu/~boyd/admm.html
4. Buzug, Thorsten M. "Computed tomography." Springer Handbook of Medical Technology. Springer, Berlin, Heidelberg, 2011. 311-342.
Potential topics of presentations include, but are not limited to:
- Computed tomography (CT) reconstruction with L1 norm or total variation (TV) norm;
CT image reconstruction via wavelet or shearlet frame based regularization
Dynamic CT reconstruction via ADMM; (The data can be download from https://arxiv.org/pdf/1802.09397.pdf )
- Various variable splitting methods;
Prerequisites: Basic mathematics and matrix algebra, basic programming skills. Basic knowledge to use Matlab is needed for completing the homework (and presentation).
Seminars are held on Mondays, 12.15-14.00 in F175a Otakaari 3.Schedule
Seminars are held on Mondays, 12.15-14.00 in F175a Otakaari 3.
9.9. Course Overview and Introduction to Computed Tomography (Zenith Purisha)
Introduction to ADMM algorithm (Rui Gao)
16.9. No lecture
23.9. Zheng Zhao (Undersampled dynamic X-ray tomography with dimension reduction Kalman filter)
30.9. Marco Soldati (Computed tomography (CT) reconstruction with L1/2 norm)
7.10. No lecture
14.10 Deadline for homework
Grading Scale: pass/fail
Registration time: 29/07/2019 9:00 – 08/09.2019 23:59