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Medical Image and Signal Processing - ELEC317

In this unit, mathematical techniques used for image analysis, image reconstruction, image improvement, information extraction and data storage will be discussed.

The focus of the first module is on image and signal quality and information metrics.

In a second module, image reconstruction methods are discussed such as Filtered back projection, Iterative image reconstruction, Fast Fourier Transform, Inverse transport equations and compressed sensing.

The third module focuses on image and signal improvement techniques such as noise reduction and filtering, deblurring, grey level renormalization, artifact compensation techniques and image deformation compensation.

In a fourth module, methods for extracting image information will be discussed such as segmentation, registration, statistical analysis, texture analysis, image based physiological modelling

The fourth module is dedicated to some advanced methods such as high performance computing and 3D and 4D medical visualization and virtual reality. Finally, concepts of big data analysis and medical image storage and management will be discussed.

Practical sessions involve the use of image visualization and reconstruction software and writing snippets of image processing software code.

Credit Points: 3
When Offered:

S2 Day - Session 2, North Ryde, Day

Staff Contact(s): Professor Yves De Deene
Prerequisites:

MATH235 and ELEC215 Prerequisite Information

Corequisites:

NCCW(s):
Unit Designation(s):

Science

Engineering

Unit Type:
Assessed As: Graded
Offered By:

Department of Engineering

Faculty of Science and Engineering

Course structures, including unit offerings, are subject to change.
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