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Unit outline_

MRTY2103: Image Optimisation and Processing

Semester 1, 2020 [Normal day] - Cumberland, Sydney

This unit of study builds upon the theory and application of Imaging Technology 1. Students will be expected to demonstrate an appreciation of image quality theory as it applies to x-ray systems, including tubes, detectors, radiation dose and display. Image processing, in both spatial and frequency domains, will be explored in an applied context so that students can optimise their practical understanding of imaging technique and image display.

Unit details and rules

Academic unit Clinical Imaging
Credit points 6
Prerequisites
? 
MRTY1037
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Ernest Ekpo, ernest.ekpo@sydney.edu.au
Lecturer(s) Ernest Ekpo, ernest.ekpo@sydney.edu.au
Will Rae, will.rae@sydney.edu.au
Terry Jones, terry.jones@sydney.edu.au
Type Description Weight Due Length
In-semester test Mid- semester exam
This is MCQ exam covering weeks 1 - 7 content
30% Week 08 I hour
Outcomes assessed: LO1 LO6 LO5 LO4 LO3 LO2
Assignment Practical reports
A reflective report of the practical activity each week.
20% Week 10 500 words
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Final exam hurdle task End of semester examination
Exam
50% Week 12 2 hours
Outcomes assessed: LO1 LO7 LO6 LO5 LO4 LO3 LO2
hurdle task = hurdle task ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to UoS and image quality Lecture (2 hr) LO3 LO5
Week 02 Image quality assessment and optimisation approaches Lecture (2 hr) LO3 LO5
Image quality assessment Practical (2 hr) LO3
Week 03 QA/QC and optimization strategies for general x-ray units Lecture (2 hr) LO2
Week 04 QA/QC and optimization strategies for CR-DR and medical displays Lecture (2 hr) LO2
Perform QA/QC for general x-ray Practical (2 hr) LO2
Week 05 Technique optimization, Reject analysis, and DRL Lecture (2 hr) LO4
Reject analysis Practical (2 hr) LO4
Week 06 System quality measurements Lecture (2 hr) LO5
System quality assessment Practical (2 hr) LO5
Week 07 Filters (Spatial and Frequency domains) Lecture (2 hr) LO6
Image filtering Practical (2 hr) LO6
Week 09 Image post-processing Lecture (2 hr) LO1 LO6
Image post-processing Practical (2 hr) LO1 LO6
Week 10 Revision of UoS content Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7

Attendance and class requirements

Attendance: Attendance at lectures and practicals is recommended. This unit uses an active learning approach, where there will be activities in class, pre-reading before class and discussion during it. Practicals are designed to integrate with and complement lectures, so the learning experience comes from the combination of these activities.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed on the Library eReserve link available on Canvas.

  • Bourne, R. (2010). Fundamentals of digital imaging in medicine. London: Springer.
  • Bushong SC (2013). Radiologic science for technologists: physics, biology and protection. ed 10, St. Louis: Mosby.
  • Pianykh OP (2013). Digital Image Quality in Medicine. London: Springer.
  • Lanca L, Silva A (2012). Digital Imaging Systems for Plain Radiography. Springer.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. apply knowledge of the fundamentals of digital imaging statistics and how they can be used to evaluate images
  • LO2. evaluate simple quality assurance principles as applied to x-ray tubes and systems and detectors
  • LO3. understand the principles of image optimization and image quality as applied specifically to plain radiographs and cross sectional images
  • LO4. understand the relationship between Dose Reference Levels and image optimization
  • LO5. understand a range of image quality metrics and system quality measures including MTF and DQE
  • LO6. apply a range of image processing techniques including filters in the spatial frequency domain and post-processing techniques
  • LO7. evaluate quality assurance principles in relation to display systems.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

Alignment with Competency standards

Outcomes Competency standards
LO1
Professional capabilities for medical radiation practice - MRPBA
1.9.f. Process image data sets.
1A.1.e. Perform image post-processing techniques.
LO2
Professional capabilities for medical radiation practice - MRPBA
1.3.d. Operate equipment and apply knowledge of laboratory procedures to practice when necessary.
1A.1.a. Operate projection radiography systems safely and effectively in a range of settings.
LO3
Professional capabilities for medical radiation practice - MRPBA
1.5.f. Perform patient/client assessment and medical radiation examination/treatment in accordance with the patient/client need and choice, legislation, registration standards, codes and guidelines.
1.9.c. Select equipment and imaging parameters relevant to the patient/client presentation and where appropriate, modify imaging parameters to achieve optimal diagnostic outcomes.
LO4
Professional capabilities for medical radiation practice - MRPBA
1A.1.a. Operate projection radiography systems safely and effectively in a range of settings.
1A.1.d. Select appropriate equipment, receptor type and set equipment geometry for the examination.
1A.2.e. Apply knowledge of imaging acquisition modes and radiation dose rates.
Domain 5.1.f. Identify radiation risks and implement effective and appropriate risk management systems and procedures.
LO5
Professional capabilities for medical radiation practice - MRPBA
1.10.a. Operate ultrasound imaging systems safely and effectively.
1.6.d. Perform the appropriate stabilisation before starting the procedure.
1A.2.e. Apply knowledge of imaging acquisition modes and radiation dose rates.
1A.3.c. Adjust relative radiation dose levels based on the range of patient/client presentations.
LO6
Professional capabilities for medical radiation practice - MRPBA
1.9.f. Process image data sets.
1A.1.e. Perform image post-processing techniques.
LO7
Professional capabilities for medical radiation practice - MRPBA
1A.1.a. Operate projection radiography systems safely and effectively in a range of settings.
1A.2.e. Apply knowledge of imaging acquisition modes and radiation dose rates.
Professional capabilities for medical radiation practice -
Competency code Taught, Practiced or Assessed Competency standard
1.3.d T P A Operate equipment and apply knowledge of laboratory procedures to practice when necessary.
1.7.b T P A Apply quality criteria to assure image quality, evaluate medical images and identify any urgent and/or unexpected findings.
1.9.c T P A Select equipment and imaging parameters relevant to the patient/client presentation and where appropriate, modify imaging parameters to achieve optimal diagnostic outcomes.
1.9.f T P A Process image data sets.
1A.1.a T P A Operate projection radiography systems safely and effectively in a range of settings.
1A.1.e T P A Perform image post-processing techniques.
1A.1.f T P A Critically evaluate images against radiographic criteria including assessment of exposure index, field of view and anatomical rotation.
1A.2.e T P A Apply knowledge of imaging acquisition modes and radiation dose rates.
1A.2.f T P A Perform image post-processing techniques. (1A.2)
Domain 5.1.d T P A Apply knowledge of radiobiology and radiation dose adjustment to deliver safe and effective patient/client outcomes.
Domain 5.1.f T P Identify radiation risks and implement effective and appropriate risk management systems and procedures.
Domain 5.3.a T P A Check and confirm that all equipment is in good order and operating within acceptable parameters.

This section outlines changes made to this unit following staff and student reviews.

We are committed to helping you have a good learning experience and have made changes to lecture content, assessments, and practical activities to capture your needs for future clinical practice based on feedback from previous students. We encourage an "open door policy", so feel free to ask questions when you are struggling to understand a concept.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.