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The University of Sydney Slide 1
OVERVIEW / MEDICAL IMAGING
Presented by
Dr Paul Wong
AMME4981/9981
Semester 1, 2016
Lecture 1
The University of Sydney Slide 2
Contact Details
Name Email Phone Room
Prof. Qing Li
(Unit of Study
Coordinator)
[email protected] 9351 8607 S509, Mechanical
Engineering
Building
Paul Wong
Andrian Sue
Phillip Tran
(Lecturers
and tutors)
9351 5674 Room 243,
Engineering Link
Building
The University of Sydney Slide 3
UOS Websites
– All course documents and announcements will be posted on the AMME website
– Assessments need to be submitted via eLearning (Blackboard)
User name: applied
Password: biomed2014
The University of Sydney Slide 4
OPENING THOUGHTS
The University of Sydney Slide 5
“As an educator, it’s my duty to empower you to think.So that you can go forth and think accurate thoughtsabout how the world is put together.”
~ Neil DeGrasse Tyson
My Motivation
The University of Sydney Slide 6
Knowledge Acquisition
– In science (and engineering), we
use mathematics to understand
physical systems
– Different fields explore different
aspects of the universe, each with
their own sets of equations,
encapsulated in theories
– Computational research has
emerged to complement
experimental methods, particularly
in research, design and
optimisation
~ Victor Eijkhout
IN VIVO
IN VITRO
IN SILICO
NATURE
Abstraction
THEORY
The University of Sydney Slide 7
COURSE OVERVIEW
The University of Sydney Slide 8
Driving Question
How does <implant> behavein the body?
The University of Sydney Slide 9
Why Use Simulations?
1. In certain cases, computational simulations are the only possible approach for analysing a problem
2. When used correctly, they make complex or unintuitive systems easier to understand
3. Conceptual design and virtual prototyping can take place early in the development cycle to optimise performance and reduce costs
The University of Sydney Slide 10
Workflow for Biomedical Problems
1. Data acquisition
• Scan region of interest
• Obtain material properties for tissues and implants
• Estimate expected loads
2. Solid modelling
• Convert image stacks into a virtual replica
• Combine with CAD model of prosthesis
3. Finite element analysis
• Generate appropriate mesh
• Characterise interaction between anatomy and prosthesis
• Verify simulation results and prosthesis design
3. Finite element analysis
• Generate appropriate mesh
• Characterise interaction between anatomy and prosthesis
• Verify simulation results and prosthesis design
The University of Sydney Slide 11
Dealing with Uncertainties
“The art of finite element analysis is modelling
materials we do not wholly understand, in shapes we cannot precisely form so as to withstand forces we cannot properly assess,
in such a way that the analyst is confident in the design with the publichaving no reason to suspect the extent of one’s ignorance.”
~ David Beneke
The University of Sydney Slide 12
STUFF I’VE BEEN WORKING ON
The University of Sydney Slide 13
Driving Question
How can we improve the design of
cochlear implants?
The University of Sydney Slide 14
› 6,092,537 DOFs
(quadratic)
› Solution time:
30 minutes<lots of code>
Model Development
ACQUIRE DATAIDENTIFY AND
SEGMENT TISSUES
The University of Sydney Slide 15
Data Visualisation
Magnitude Direction Neural Response
The University of Sydney Slide 16
MEDICAL IMAGING
The University of Sydney Slide 17
Required Modelling Inputs
Geometry
• What does it look like?
Material Properties
• What is it made of?
Loads
• What forces is it being subjected to?
Boundary Conditions
• What is happening at the system boundary?
The University of Sydney Slide 18
Imaging Requirements
Critical
– Imaging technique must clearly
show the region of interest
– Data must be volumetric
Desirable
– High resolution
– Strong contrast between tissues
– Free of artefacts
– Isotropic grid
The University of Sydney Slide 19
Computed Tomography
Theory
– Developed by Sir Godfrey
Newbold Hounsfield and Allan
McLeod Cormack
– Structures with higher densities
absorb more x-rays than those
with lower densities
– Image brightness measures amount
of x-rays absorbed by an object
– Depends on duration and
strength of the x-ray beam,
other scan parameters
The University of Sydney Slide 20
Computed Tomography
Hounsfield Unit Scale
– Linear transformation of
attenuation coefficients (i.e. how
difficult it is for the x-rays to
penetrate a material)
– Calibration references:
– 0 HU: radiodensity of distilled
water at STP
– -1000 HU: radiodensity of air
at STP
– A 1 HU change represents a 0.1%
difference of the attenuation
coefficient of water (μair ≈ 0)
Substance HU
Air -1000
Fat -120
Water 0
Blood 30–45
Muscle 40
Contrast medium 130
Bone 400+
The University of Sydney Slide 21
Computed Tomography
Practice
– A series of x-ray images is taken
around an axis of rotation
– Computers process the raw 2D
slices to give a 3D representation
of the structures inside the scanned
body
– The 3D structures are then
converted back into a stack of
orthogonal 2D images
– Clinical, micro, and nano variants
The University of Sydney Slide 22
Computed Tomography
Usage Considerations
– Ideal for objects that can be distinguished by density
– Simple threshold-based tools can then be used to identify and separate them
– Not great for separating different types of soft tissue
– Metal artefacts
– High density objects tend to obscure those with lower densities
– Geometric information becomes hidden (but not distorted)
– Best to avoid scanning low and high density objects together
– Stronger radiation levels can overcome this, but must not exceed safety limits
– Due to the use of ionising radiation, extended exposure should be avoided for live subjects
The University of Sydney Slide 23
Computed Tomography
Examination Type Typical Effective Dose (mSv)
Personnel security screening 0.00025
Chest x-ray 0.1
Head CT 1.5
Screening mammography 3
Abdomen CT 5.3
Chest CT 5.8
Virtual (CT) colonoscopy 3.6-8.8
Chest, abdomen and pelvis CT 9.9
Cardiac CT angiogram 6.7-13
Barium enema 15
Neonatal abdominal CT 20
The University of Sydney Slide 24
Magnetic Resonance Imaging
Theory
– An electromagnetic field is
applied at the resonant frequency
of hydrogen protons, changing
their orientation
– When the field is removed, they
realign with the static magnetic
field, emitting a radio frequency
signal that is detected
– Image brightness corresponds to
density of hydrogen in a region
The University of Sydney Slide 25
Magnetic Resonance Imaging
Variants
– Targeting different relaxation times emphasises different structures:
– T1: Fat and large molecules
– T2: Fluids and diseased tissues
– Proton density: Urine, CSF
– Diffusion MRI: Maps diffusion of water through tissues (anisotropy)
The University of Sydney Slide 26
Magnetic Resonance Imaging
Usage Considerations
– Ideal for distinguishing between soft tissues due to texture
– Threshold based segmentation may not work well due to similar grey levels
– Often exhibit signal attenuation and/or noise near borders of image
– No known significant impact on health
– More expensive than CT
– Metallic objects will not influence the image, but magnetic objects will cause distortions
– Electronic components (e.g. pacemakers) may be damaged
The University of Sydney Slide 27
Image Comparison
CT MRI
The University of Sydney Slide 28
Histology
– Slides prepared from tissue
sample and imaged using a
microscope
– High resolution provides plenty of
detail
– Tissues can be distinguished using
cell staining techniques
– Destructive since specimen must be
divided into thin slices
– Artefacts from slicing process
The University of Sydney Slide 29
Serial Photography
– Sample embedded in gel, frozen
and photographs taken at set
intervals
– Good for larger samples
– Extra information encoded in
colour
– Loss of contrast when
converted to greyscale
– Destructive since specimen must be
divided into thin slices
– Artefacts from grinding process
The University of Sydney Slide 30
Thin-Sheet Laser Imaging Microscopy
– Specimen is chemically treated to
make it translucent
– A laser light sheet is passed
through the sample and an image
taken perpendicular to the plane
– Very high resolution
– Non-destructive
– Long treatment time
– Shadow artefacts
The University of Sydney Slide 31
Summary
– Different imaging techniques capture different types of information
– Each has its relative strengths and weaknesses, so choose one that is suitable for your purposes
– It is possible to combine multiple datasets, but requires additional planning, effort, and cost
The University of Sydney Slide 32
GROUP PROJECTS
The University of Sydney Slide 33
Project Overview
People Timeframe
1-2 Week 3
3-5 Week 7
3-4 Week 12
Image
Processing
Modelling
and Design
Experimental
Validation
The University of Sydney Slide 34
Teams and Topics
Transarticular screw fixation Dental bridges
Dental implantsSkull plate fixation
The University of Sydney Slide 35
Tips for a Successful Project
– Exercise in project planning
– Establish your aims and scope early on
– Distribute the workload according to strengths
– Pull your weight (i.e. don’t be “that guy”)
– Have redundancies in case of “missing” group members
– Plan ahead to validate the model
“If you reach for the stars, you might not quite get one, but you
won’t end up with a handful of mud, either.”
~ Leo Burnett
The University of Sydney Slide 36
DISCUSSION TIME