Credits: 3

Schedule: 09.09.2019 - 14.10.2019

Contact information for the course (applies in this implementation): 

By email at zenith.purisha@aalto.fi and rui.gao@aalto.fi

 

 

Details on the course content (applies in this implementation): 

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 competence to work independently on the selected topic

In every seminar talk, there is the author 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 should send the summary paper to the opponent and to the teachers on the thursday preceding the presentation day. The slides should be sent to the teacher 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.

 

 

Elaboration of the evaluation criteria and methods, and acquainting students with the evaluation (applies in this implementation): 

Grading: pass/fail.

 

To pass the course, attendance in all of part of seminars is compulsory.

Details on calculating the workload (applies in this implementation): 

10-12 h contact teaching, 50-60 h independent studies.

 

Details on the course materials (applies in this implementation): 

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.


Prerequisites: Basic mathematics and matrix algebra, basic programming skills. Basic knowledge to use Matlab is needed for completing the presentation and homework.

Additional information for the course (applies in this implementation): 

Potential topics of presentations include, but are not limited to:

  • Computed tomography (CT) reconstruction with L1 norm or total variation (TV) norm;
  • Dynamic CT reconstruction via ADMM; (The data can be download from https://arxiv.org/pdf/1802.09397.pdf )
  • Various variable splitting methods;



Details on the schedule (applies in this implementation): 

Same as "time and place" section.

Description

Registration and further information