成人大片

ELEC ENG 7113 - Principles of Medical Imaging

North Terrace Campus - Semester 2 - 2023

In this course, students will gain an understanding of the physical principles involved in a broad range of medical imaging modalities, including X-rays, ultrasound, and nuclear magnetic resonance. Students will develop a critical knowledge on the signal processing approaches used to reconstruct images from measured data and how measurement parameters affect the image contrast.

  • General Course Information
    Course Details
    Course Code ELEC ENG 7113
    Course Principles of Medical Imaging
    Coordinating Unit School of Electrical & Electronic Engineering
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hours per week
    Available for Study Abroad and Exchange Y
    Assumed Knowledge Engineering mathematics at undergraduate level
    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 (Wednesdays 12-2pm)
    Practicals occur weekly throughout the semester.
    There are:
    3 Matlab workshops on image processing,
    2 interviews,
    a group project,
    and tutorials (numerical questions related to each medical imaging modality).

    3. In-class tests
    Tests occur in scheduled times (Wednesdays 12-2pm) in weeks 8 and 12.
  • 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 3.6
    University 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.

    1-3
  • 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. https://link.springer.com/book/10.1007/978-3-030-30511-6
    3. Andreas Maier, Stefan Steidl, Vincent Christlein, Joachim Hornegger (Eds.) Medical Imaging Systems: An Introductory Guide. https://doi.org/10.1007/978-3-319-96520-8
    Online Learning
    This course uses a variety of online resources to support learning, including:
    slides, videos, example code and tutorial questions

    All course announcements will be made via the MyUni site.

    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
    Lectures  In-person or pre-recorded lectures 6 to 12 24
    Group project  Report (include literature review of recent journal publications) and presentation
    5 to 10

    40-50
    Tutorials on numerical problems 5 x 1-hr sessions 5 15
    Interviews  2 interviews organised by the master student 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)

    Laboratory clothing restrictions apply to the lab/facility tour sessions: closed-toe shoes.
    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:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. 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 interview 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 .

  • 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.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.