Neuroimaging Methods and Applications

Subject 421-631 (2008)

Note: This is an archived Handbook entry from 2008.Search for this in the current handbook

Credit Points: 12.500
Level: Graduate/Postgraduate
Dates & Locations:

This subject has the following teaching availabilities in 2008:

Semester 1, - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours of contact time including, 24 hours of lectures and 12 hours of tutorials/supervised learning sessions. 84 hours non-contact time commitment
Total Time Commitment: Not available
Prerequisites: None
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support:

Subject Overview: This subject introduces students to modelling and analysis techniques used in brain imaging research, based on magnetic resonance imaging (MRI) data. The course will include: introduction to Matlab programming; basic techniques for analysing structural, functional and diffusion MR images; techniques for modelling functional MR time series datasets.
Assessment: One 2-hour examination (40%) and three computer laboratory projects (20% each).
Prescribed Texts: None
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills: The course objectives are to train students in the principles and practice of modelling and analysing MRI data in the context of neuroscience research. The course will provide students with a detailed understanding of MRI image processing, including structural, functional and diffusion MR data. Students will be instructed in the use of Matlab for image analysis, and will utilise this understanding to complete three computer based projects.
Related Course(s): Master of Biomedical Engineering
Master of Engineering Science(Biomedical Enginering)

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