Class meeting time: Sunday starting at 4:00p - BME 3201 auditorium
Attendance is required for all lectures - Attending 85% of classes is required to pass the course NO EXCEPTIONS
Intended Learning Objectives (ILOs)
To build a strong theoretical and practical implementation skills for medical image reconstruction. This is an advanced course and therefore will cover advanced topics immediately from the start.
A number of sources from textbooks and research papers will be handed out for each lecture
100% on Class Projects and Final Project
Course Topics to be Covered (Tentative)
(text file, target image size should be128x128, each row is one sample, four numbers on each row for normalized (kx,ky) and their complex k-space data value, format: "kx value" "ky value" "real part of k-space" "imaginary part of k-space").
(text file, k-space size: 256x256, each row is one sample with real and imaginary parts, 2D k-space written in sequence row by row)
(each is written in binary form - information about organization of data is included inside each archive - choose one archive only to work on)
Send mail to ymk (at) k-space.org with
questions or comments about this site.