ELEC ENG 3113 - Principles of Medical Imaging
North Terrace Campus - Semester 2 - 2023
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General Course Information
Course Details
Course Code ELEC ENG 3113 Course Principles of Medical Imaging Coordinating Unit School of Electrical & Electronic Engineering Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange Y Assumed Knowledge Maths 1A,1B, ENG 3101 Assessment exam, in-class quiz, assignments, tutorial Course Staff
Course Coordinator: Associate Professor Jiawen Li
Course Timetable
The full timetable of all activities for this course can be accessed from .
1. Lectures
In-person (Weeks 1,8,9,10,11,12) or pre-recorded (Weeks 2-7) lectures that present the theory for each medical imaging modality are scheduled for each week.
2. Practicals
Practicals occur weekly throughout the semester.
There are:
3 Matlab workshops on image processing,
2 facility tours,
a group project,
and tutorials (numerical questions related to each medical imaging modality).
3. In-class tests
Tests occur in scheduled times in weeks 8 and 12.
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Learning Outcomes
Course Learning Outcomes
1. Be able to demonstrate a firm understanding of various medical imaging modalities from an engineering perspective;
2. Be able to articulate the biomedical applications and limitations of various imaging technologies;
3. Be able to demonstrate creative and critical thinking about biomedical imaging technologies through reports and group presentation.
The above course learning outcomes are aligned with the
The course is designed to develop the following Elements of Competency: 1.1 1.2 1.3 1.4 1.5 2.1 2.2 3.2 3.4 3.5 3.6University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
1-2 Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
3 Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
3 Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
2-3 Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
1 Attribute 8: Self-awareness and emotional intelligence
Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.
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Learning Resources
Required Resources
All required resources are provided on MyUni.Recommended Resources
Recommended textbooks if you are interested to learn more about medical imaging:
1. Jerrold T. Bushberg, J. Antony Seibert, Edwin M. Leidholdt, Jr. and John M. Boone. The Essential Physics of Medical Imaging. ISBN 0-683-30118-7.
2. Michael Chappell, Principles of Medical Imaging for Engineers: From Signals to Images.
3. Andreas Maier, Stefan Steidl, Vincent Christlein, Joachim Hornegger (Eds.) Medical Imaging Systems: An Introductory Guide.Online Learning
This course uses a variety of online resources to support learning, including:
- slides, videos, example code and tutorial questions
The course gradebook will be used to return continuous assessment marks. Students should check the gradebook regularly and confirm their marks have been correctly entered. -
Learning & Teaching Activities
Learning & Teaching Modes
This course uses face-to-face tutorials, group project, workshops and lab/facility tours, supplemented by online materials, to achieve its learning objectives.
The in-person and pre-recorded presentations focus on key concepts and are supported by tutorials where practice exercises are discussed to test and develop understanding. Students will work on a clinical imaging project in small groups to consolidate understanding of various imaging modalities. There is a small assessment component for active participation in tutorials. Workshops provide an opportunity to develop hands-on skills in image processing and the tasks are typically completed in Matlab. Lab/facility tours allow students to see various biomedical imaging devices.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
There will be approximately 30 contact hours throughout the course. Students are expected to spend approximately 120 hours of private study, completing assignments and revising for tests.
Activity Detail Contact Hours Workload Hours Lectures In-person or pre-recorded lectures 6 to 12 24 Group project Report and presentation 5 to 10 40 Tutorials on numerical problems 5 x 1-hr sessions 5 15 Lab/facility tours 2-3 tours 2 to 6 12 Matlab workshops on image processing 3 x 1-hr sessions 3 6 In-class tests 2 x 1-hr sessions 2 24
Learning Activities Summary
Week 1 Introduction
Week 2 X Ray and CT
Week 3 Image Processing
Week 4 Nuclear Medicine Imaging
Week 5 Magnetic Resonance Imaging 1
Week 6 Magnetic Resonance Imaging 2
Week 7 Ultrasound Imaging
Week 8 Fundamentals of Optics and Photonics
Week 9 Endoscopy and optical design (guest lecture by Prof Alois Herkommer)
Week 10 Advanced Microscopy (guest lecture by Prof Kishan Dholakia)
Week 11 From Bench to Bedside (guest lecture by Prof Robert McLaughlin)
Week 12 Machine Learning and Medical Imaging (guest lecture by frontline clinician and AIML deputy director Dr Johan Verjans)Specific Course Requirements
Laboratory clothing restrictions apply to the lab/facility tour sessions: closed-toe shoes. -
Assessment
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
Assessment Task Weighting (%) Individual/ Group Due (week)* Hurdle criteria Practicals 20 Individual 1,3,5,7,11 Quizzes 10 Individual 2,4,6,9,10 Group project 35 Group 9,10,12 40% In-class tests 30 Individual 8,12 40% Participation at guest lectures 5 Individual 9-12
* The specific due date for each assessment task will be available on MyUni.
This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.Assessment Related Requirements
A hurdle requirement is defined by the University's Assessment for Coursework Programs policy as "...an assessment task mandating a minimum level of performance as a condition of passing the course.Assessment Detail
No information currently available.
Submission
Active participation in tutorials and workshops are assessed in session. Written assignments (e.g., group report and facility tour reports) are submitted online via MyUni.Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through .
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Student Feedback
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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