Outline

Overview

This unit of study builds upon the theory and application of MRTY1037, Imaging Technology 1. Students will be expected to demonstrate a deeper understanding of image quality as it applies to X-ray systems, including the performance of X-ray tubes, detectors, and displays, as well as the relation between radiation dose and image quality. Image processing will be examined in both spatial and frequency domains in an applied context so that students can optimise their practical understanding of imaging technique and image display. Additionally, students will explore other advanced concepts such as Modulation Transfer Function (MTF) and Detective Quantum Efficiency (DQE) to evaluate and improve system performance. Key quality assurance (QA) principles and optimisation strategies will be applied to ensure consistent image quality and radiation safety.

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	Sahand Hooshmand, sahand.hooshmand@sydney.edu.au
Lecturer(s)	Steven Meikle, steven.meikle@sydney.edu.au
	Jillian Clarke, jillian.clarke@sydney.edu.au
	Patrick Brennan, patrick.brennan@sydney.edu.au
	Sahand Hooshmand, sahand.hooshmand@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Assignment	Practical Reports A reflective report for each practical activity for all tutorial weeks.	30%	Multiple weeks	Maximum of 500 words per report.
Outcomes assessed:
Online task	Early Feedback Tast (EFT) MCQs	5%	Week 03 Due date: 14 Mar 2025 at 17:00	30 minutes
Outcomes assessed:
Supervised test ?	Mid Semester Examination 30 MCQs, each worth 1 mark.	30%	Week 07 Due date: 07 Apr 2025 at 15:00	1 hour
Outcomes assessed:
Supervised exam ?	End of Semester Exam SAQs and LAQs	35%	Week 12 Due date: 23 May 2025 at 14:30	2 hours
Outcomes assessed:

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Assessment 1: Midsemester exam is an individual exam consisting of 30MCQs. This contributes 30% to the final mark.

Assessment 2: Practical report of weekly tutorial activities. This contributes 20% to the final marks.

Assessment 3: Assignments contributing 50% to the final mark.

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.

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

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late submission of practical reports attracts a penalty and depends on how late the submission is received. Replacement exams must be approved by the relevant authority and the UoS coordinator.

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.

Learning support

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Picture This: What is an Image?	Lecture (2 hr)
Week 02	The Ingredients of Image Quality	Lecture (2 hr)
Week 03	How Digital Images Are Made	Lecture and tutorial (4 hr)
Week 04	Ultrasound Image Quality	Lecture (2 hr)
Week 05	Imaging System Quality Measures	Lecture and tutorial (4 hr)
Week 06	Frequency Domain Filters	Lecture (2 hr)
Week 07	Spatial Domain Filters	Lecture and tutorial (4 hr)
Week 08	Maintaining Image Quality	Lecture (2 hr)
Week 09	Reject Analysis and DRLs	Lecture and tutorial (4 hr)
Week 10	Clinical Image Quality Assessment	Lecture and tutorial (4 hr)
Week 11	Physical Image Quality Assessment	Lecture and tutorial (4 hr)
Week 12	Revision	Lecture (2 hr)

Attendance and class requirements

Attendance: Lectures and tutorials are face-to-face. This unit uses an in-person learning approach, where students are encouraged to attend classes to facilitate learning and activities, with opportunities to ask questions. Tutorials 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

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
LO7. Apply post-processing techniques to improve image quality
LO8. Understand image quality in ultrasound and computed tomography

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
Learning outcomes

Alignment with Competency standards

Outcomes	Competency standards
	Professional capabilities for medical radiation practice - 1.9.f. Process image data sets. 1A.1.d. Select appropriate equipment, receptor type and set equipment geometry for the examination. 1A.2.d. Apply knowledge of equipment geometry for procedures. 1A.2.f. Perform image post-processing techniques. (1A.2) Domain 5.1.f. Identify radiation risks and implement effective and appropriate risk management systems and procedures.
	Professional capabilities for medical radiation practice - Domain 5.3.a. Check and confirm that all equipment is in good order and operating within acceptable parameters. Domain 5.3.b. Follow protocols to record details of all routine equipment checks. Domain 5.3.c. Identify and take appropriate action to correct unacceptable condition or operation of all equipment. Domain 5.3.d. Follow protocols to record and report non-conformance of all equipment.
	Professional capabilities for medical radiation practice - 1.3.d. Operate equipment and apply knowledge of laboratory procedures to practice when necessary. 1.7.b. Apply quality criteria to assure image quality, evaluate medical images and identify any urgent and/or unexpected findings. 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. 1A.1.f. Critically evaluate images against radiographic criteria including assessment of exposure index, field of view and anatomical rotation. 1A.2.e. Apply knowledge of imaging acquisition modes and radiation dose rates. Domain 5.1.c. Apply knowledge of radiobiology and medical radiation physics to examinations/treatment. Domain 5.1.d. Apply knowledge of radiobiology and radiation dose adjustment to deliver safe and effective patient/client outcomes. Domain 5.1.f. Identify radiation risks and implement effective and appropriate risk management systems and procedures.
	Professional capabilities for medical radiation practice - 1A.3.c. Adjust relative radiation dose levels based on the range of patient/client presentations. Domain 5.3.d. Follow protocols to record and report non-conformance of all equipment.
	Professional capabilities for medical radiation practice - 1A.1.f. Critically evaluate images against radiographic criteria including assessment of exposure index, field of view and anatomical rotation. Domain 5.3.c. Identify and take appropriate action to correct unacceptable condition or operation of all equipment.
	Professional capabilities for medical radiation practice - Domain 5.1.c. Apply knowledge of radiobiology and medical radiation physics to examinations/treatment. Domain 5.3.a. Check and confirm that all equipment is in good order and operating within acceptable parameters. Domain 5.3.b. Follow protocols to record details of all routine equipment checks. Domain 5.3.c. Identify and take appropriate action to correct unacceptable condition or operation of all equipment. Domain 5.3.d. Follow protocols to record and report non-conformance of all equipment.

Responding to student feedback

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

We are committed to helping you have a good learning experience. Therefore, we continuously make changes to lecture content, assessments, and tutorial 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.

Additional information

Canvas

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

MRTY2103: Image Optimisation and Processing

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links