MRS527 Artificial Intelligence and Image Analysis (8)

This subject explores the advanced concepts and innovations associated with artificial intelligence, neural network algorithms, machine learning and deep learning in medical image analysis. It will examine the foundation principles and explore the landscape associated with these concepts in artificial intelligence. The applications of machine learning and deep learning will be investigated, with the opportunity to critically discuss relevant concepts within the context of clinical and research medical image analysis. The subject aims to arm students with foundation understanding of the principles and working knowledge of artificial intelligence in medical image analysis.

Availability

Session 1 (30)
Online
Wagga Wagga Campus

Continuing students should consult the SAL for current offering details: MRS527. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System

HD/FL

Duration

One session

School

School of Dentistry and Medical Sciences

Assumed Knowledge

Undergraduate degree and clinical experience in medical radiation sciences.

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to investigate and apply advanced knowledge of the principles and applications of artificial intelligence in medical image analysis;
  • be able to critically discuss the principles and technologies underpinning neural networks, machine learning, and deep learning in medical image analysis;
  • be able to identify, justify and evaluate opportunities for, and applications of, artificial intelligence augmented medical image analysis;
  • be able to develop robust artificial intelligence frameworks to support decision making and application of algorithms in medical image analysis;
  • be able to design, evaluate and implement an artificial intelligence application for medical image analysis;
  • be able to demonstrate command of, and critically reflect on the legal, social and ethical implications of artificial intelligence in image analysis and appraise applications or proposals within this context; and
  • be able to apply principles of artificial intelligence in medical image analysis within the clinical and research environments.

Syllabus

This subject will cover the following topics:
  • MODULE 1: PRINCIPLES OF ARTIFICIAL INTELLIGENCE
  • Understanding artificial intelligence ecosystem in image analysis;
  • Artificial neural networks and machine learning; and
  • Convolutional neural networks and deep learning.
  • MODULE 2: APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN IMAGE ANALYSIS
  • Understanding artificial intelligence landscape in image analysis;
  • Classification, segmentation, detection and localisation tools;
  • Intelligent imaging applications in image analysis;
  • Ethical challenges of artificial intelligence in image analysis; and
  • Developing an artificial intelligence project.

The information contained in the CSU Handbook was accurate at the date of publication: June 2022. The University reserves the right to vary the information at any time without notice.

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