Course coordinator
Professor Markus Barth
Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Modern medical imaging technologies and applications. Lectures cover signal principles, image formation, and instrumentation for X-rays, Computerised Tomography (CT), Single Photon Emission Tomography (SPECT), Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI).
This course aims to expose engineers and scientists to a wide range of currently employed technologies for medical imaging. The class emphasizes that the ongoing advancements in medical imaging rely heavily on the innovation and expertise of engineers and scientists. The lectures will delve into the origins of signals, techniques, and instrumentation necessary for generating medical images. The imaging modalities covered will include X-Ray, Computerized Tomography (CT), Ultrasound, Magnetic Resonance Imaging (MRI), Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET).
By the end of the course, students are expected to:
- Understand the underlying principles of medical imaging systems.
- Develop numerical algorithms based on these principles to generate medical images.
- Implement selected algorithms using programming tools such as MATLAB.
- Critically evaluate the effectiveness of standard imaging techniques.
- Recognize the potential risks and side effects of different techniques and materials.
- Identify suitable imaging techniques for various simple clinical scenarios.
- Comprehend the opportunities and technical challenges associated with the covered imaging systems.
- Independently gather information from diverse sources (e.g., books, journal publications, electronic application notes, company product data sheets, etc.).
Course Changes in Response to Previous Student Feedback
We will extend invitations to experts in the field of medical imaging and clinical applications to present guest lectures on the latest advancements and technologies.
Course requirements
Assumed background
Basic signal/image processing concepts such as Fourier Transform.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
ELEC3004 or BIOE6901 or BIOE3001
Incompatible
You can't enrol in this course if you've already completed the following:
ELEC6601 or ELEC4601 or ELEC7606
Course contact
Course staff
Lecturer
Professor Markus Barth
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
This course is intended to expose engineers and scientists to the broad range of currently employed technologies for medical imaging. It is emphasized in the class that the rapid advances made in medical imaging continue to depend on the innovation and expertise of engineers and scientists. The lectures will explore the origins of the signals, techniques and instrumentation necessary to form medical images. The imaging modalities will cover X-Ray, Computerized Tomography (CT), Ultrasound, Magnetic Resonance Imaging (MRI), Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET).
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Evaluate the underlying principles of medical imaging systems
LO2.
Formulate numerical algorithms to generate medical images based on these principles.
LO3.
Design and implement algorithms using programming tools like MATLAB
LO4.
Critique the utility of standard imaging techniques
LO5.
Assess the risks and side effects of techniques and materials used.
LO6.
Determine appropriate imaging techniques for various simple clinical scenarios.
LO7.
Analyse the opportunities and technical challenges of the covered imaging systems.
LO8.
Synthesize information independently from diverse resources.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Quiz |
Nuclear Medicine Imaging
|
10% |
30/08/2024 3:00 pm |
| Computer Code, Paper/ Report/ Annotation | Computerised Tomography Reconstruction | 20% |
13/09/2024 3:00 pm |
| Computer Code, Paper/ Report/ Annotation | Magnetic Resonance Imaging Reconstruction | 20% |
18/10/2024 3:00 pm |
| Examination |
Final Examination
|
50% |
End of Semester Exam Period 2/11/2024 - 16/11/2024 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Nuclear Medicine Imaging
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 10%
- Due date
30/08/2024 3:00 pm
- Learning outcomes
- L01, L04, L05, L07
Task description
This is an individual assessment and students are expected to work independently. There will be 10 short multiple choice questions online related to nuclear medicine imaging. These questions weigh 10% of the final grade. Students can attempt as many times as they like to learn the content.
Submission guidelines
Deferral or extension
You may be able to defer this exam.
An alternative quiz will be available for students who cannot submit by the due date.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
An alternative quiz will be available for students who cannot submit by the due date.
Computerised Tomography Reconstruction
- Mode
- Written
- Category
- Computer Code, Paper/ Report/ Annotation
- Weight
- 20%
- Due date
13/09/2024 3:00 pm
- Learning outcomes
- L02, L03, L08
Task description
Students will submit a project report (as an MS Word file) and functional Matlab code for assessment. The Matlab code should be written in a way that the lecturer should be able to run it without modifications or entering any parameters. If the Matlab code does not produce the results shown in the report, students will not receive any credit for the corresponding section(s) of the report. This is an individual assessment and students are expected to work independently.
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Marked assignments with feedback and/or detailed solutions with feedback will be released to students between 7-21 days where the earlier time frame applies if no extensions.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Magnetic Resonance Imaging Reconstruction
- Mode
- Written
- Category
- Computer Code, Paper/ Report/ Annotation
- Weight
- 20%
- Due date
18/10/2024 3:00 pm
- Learning outcomes
- L02, L03, L08
Task description
Students will submit a project report (as an MS Word file) and functional Matlab code for assessment. The Matlab code should be written in a way that the lecturer should be able to run it without modifications or entering any parameters. If the Matlab code does not produce the results shown in the report, students will not receive any credit for the corresponding section(s) of the report.
This is an individual assessment and students are expected to work independently.
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Marked assignments with feedback and/or detailed solutions with feedback will be released to students between 7-21 days where the earlier time frame applies if no extensions.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Final Examination
- Hurdle
- Identity Verified
- Mode
- Written
- Category
- Examination
- Weight
- 50%
- Due date
End of Semester Exam Period
2/11/2024 - 16/11/2024
- Learning outcomes
- L01, L04, L05, L06, L07
Hurdle requirements
To pass the course, 50% or above must be achieved in the final exam.ﾠExam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed Book examination - no written materials permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 19 |
Absence of evidence of achievement of course learning outcomes. Course grade description: Fails to demonstrate most or all of the basic requirements of the course. Serious deficiencies in the quality of performance in relation to learning objectives. Fails to satisfy most or all of the basic requirements of the course. |
| 2 (Fail) | 20 - 44 |
Minimal evidence of achievement of course learning outcomes. Course grade description: Demonstrates clear deficiencies in understanding and applying fundamental concepts; communicates information or ideas in ways that are frequently incomplete or confusing and give little attention to the conventions of the discipline. Fails to satisfy some of the basic requirements of the course. Clear deficiencies in performance, but evidence that some basic requirements have been met. The minimum percentage required for a grade of 2 is: 20% |
| 3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Demonstrates superficial or partial or faulty understanding of the fundamental concepts of the field of study and limited ability to apply these concepts; presents undeveloped or inappropriate or unsupported arguments; communicates information or ideas with lack of clarity and inconsistent adherence to the conventions of the discipline. Falls short of satisfying all the requirements for a Pass. The minimum percentage required for a grade of 3 is: 45% |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Demonstrates adequate understanding and application of the fundamental concepts of the field of study; develops routine arguments or decisions and provides acceptable justification; communicates information and ideas adequately in terms of the conventions of the discipline. Satisfies all of the basic learning requirements for the course, such as knowledge of fundamental concepts and performance of basic skills; demonstrates sufficient quality of performance to be considered satisfactory or adequate or competent or capable in the course. The minimum percentage required for a grade of 4 is: 50% |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Demonstrates substantial understanding of fundamental concepts of the field of study and ability to apply these concepts in a variety of contexts; develops or adapts convincing arguments and provides coherent justification; communicates information and ideas clearly and fluently in terms of the conventions of the discipline. Demonstrates ability to use and apply fundamental concepts and skills of the course, going beyond mere replication of content knowledge or skill to show understanding of key ideas, awareness of their relevance, some use of analytical skills, and some originality or insight. The minimum percentage required for a grade of 5 is: 65% |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: As for 5, with frequent evidence of originality in defining and analysing issues or problems and in creating solutions; uses a level, style and means of communication appropriate to the discipline and the audience. Demonstrates awareness and understanding of deeper and subtler aspects of the course, such as ability to identify and debate critical issues or problems, ability to solve non-routine problems, ability to adapt and apply ideas to new situations, and ability to invent and evaluate new ideas. The minimum percentage required for a grade of 6 is: 75% |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: As for 6, with consistent evidence of substantial originality and insight in identifying, generating and communicating competing arguments, perspectives or problem-solving approaches; critically evaluates problems, their solutions and implications. Demonstrates imagination, originality or flair, based on proficiency in all the learning objectives for the course; work is interesting or surprising or exciting or challenging or erudite. The minimum percentage required for a grade of 7 is: 85% |
Additional course grading information
To pass the course (i.e., grade 4 and above), 50% or above must be achieved in the final exam; otherwise a grade not exceeding a 3 will be recorded.ﾠ
A grade of 7 (High Distinction) requires 65% or above in all assessment items; otherwise a grade not exceeding a 6 will be recorded.ﾠ
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Use of AI Tools
This task has been designed to be challenging, authentic and complex. ﾠWhilst students may use AI technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI tools.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Lectures Medical Imaging Radiographic Imaging (Week 1 - Week 3) Nuclear Medicine Imaging (Week 4 - Week 5) Ultrasound Imaging (Week 6 - Week 7) Magnetic Resonance Imaging (Week 8 - Week 13) Learning outcomes: L01, L04, L05, L06, L07 |
Tutorial |
Tutorials Medical Imaging Radiographic Imaging (Week 1 - Week 3) Nuclear Medicine Imaging (Week 4 - Week 5) Ultrasound Imaging (Week 6 - Week 7) Magnetic Resonance Imaging (Week 8 - Week 13) Learning outcomes: L02, L03, L04, L05, L06, L08 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: