The CMI Cardiac Action Potential Imaging System An Arrhythmia Research Tool

1
The CMI Cardiac Action Potential Imaging System
An Arrhythmia Research Tool
-- Making it the Biomedical Way
BC Research Institute for Childrens and Womens
Health Simon Fraser University
2
Agenda

• Introduction
• Background
• Technical Features Future Improvements
• Business Component
• Conclusion
• QA

3
Introduction System Overview
Optical Pathway
Imaging Device
Image Processing
Image Generation
Image Acquisition
Image Analysis
4
Introduction CMI Executive Team
Seddrak Luu President
Ronnie Chan CEO
Yindar Chuo CFO
Allen Lai CMO
Deanna Lee COO
Edwin Wong CTO Hardware
Jimmy Tsui CTO Firmware
Stephen Wong CTO Software
5
Introduction Sources of Information
Dr. Andrew Rawicz
Dr. Glen Tibbits
Dr. M. Faisal Beg
Haruyo Kashihara Eric Lin School of
Kinesiology School of Engineering Science
6
Background Arrhythmia

• Junctional Ectopic Tachycardia
• Disorders of the regular rhythmic beating of the
  heart
• Occur in children after open heart surgery
• 1 in 10 infants goes into arrhythmia after open
  heart surgery
• Can be lethal

7
Background Our Goal

• Develop CAPIS to help understand the arrhythmia
• Focus on helping those in need

8
Technical Features of CAPIS
-- Making it the Biomedical Way
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Technical Features of CAPIS
-- Making it the Biomedical Way

• Image Generation Module
• Image Acquisition Module
• Image Analysis Module

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Image Generation Module Setup

• Mercury Arc Lamp

• Mercury Arc Lamp and Blue LED

• Heart cell solution

• Rabbit Heart

• Mirrors and filters in multiviewer

• Mirrors and filters in microscope

• Stimulator

• Photomultiplier Tubes

Current Setup
Original Setup

• LabVIEW software

11
Image Generation Module Cell Preparation

• Heart cell extraction from 20-day-old rabbit
• Addition of dye and calcium
• Pipette solution into bath
• Connect wires from bath to stimulator

Bath
Bath secured on holder
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Image Generation Module Optical Pathway

• Cells are exposed to filtered light source
• Stimulator is turned on
• Cell contracts, emits light from fluorescence
• PMT captures green/red photons in form of TTL
  pulses

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Image Generation Module Cell Contraction
Finding Healthy Contracting Cells

• Cell should be elongated (as opposed to round)
• Cell should have striations
• Neighbouring cells should not crowd or overlap
  contracting cell to optimize signal-to-noise
  ratio when capturing its fluorescence
• Cell contracts by shrinking approx. 15 at each
  end

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Image Generation Module Cell Contraction
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Image Generation Module Results

• Mercury Arc Lamp
• Cell receives correctly filtered excitation beam
• Cell contracts and fluoresces under stimulation
  and excitation

• Blue LED
• Cell receives correctly filtered excitation beam
• Not enough power to observe contractions

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Image Generation Module Results
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Image Generation Module Results

• Software
• TTL pulses from PMT can be counted by software
• Software can output ratiometric info to text file
• Software can measure frequency, but tradeoff
  exists between sensitivity and accuracy
• Ratiometric data collected by software does not
  agree with anticipated results

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Image Generation Module Results
Possible causes for results not meeting
expectations

• Found very few healthy cells, and most of those
  found to be overlapped, causing poor
  signal-to-noise ratio
• Time constraint to conduct experiments and
  collecting data
• Experimental techniques may be a factor
• Software may lack accuracy in producing our
  expected results

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Image Generation Module Feasibility
Further steps necessary to ensure feasibility

• Additional observations of healthy cells
• Ensure the software produces results accurate
  enough to meet our needs

20
Technical Features of CAPIS
-- Making it the Biomedical Way

• Image Generation Module
• Image Acquisition Module
• Image Analysis Module

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Image Acquisition Module Development Overview

• Module goal for proof-of-concept phase
• Design and functionality overview and
  verification
• Performance analysis for benchmarking
• Recommendations drawn from analysis
• Future considerations

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Image Acquisition Module Goals (1)

• The concept being proved
• Image capture and display
• Approach to verifying the concept
• Available resources

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Image Acquisition Module Goals (2)
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Image Acquisition Module Functionality Overview

• Input requirement
• Physical requirement
• Image capturing performance requirement
• Image display performance requirement
• General requirement

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Image Acquisition Module Design Overview (1)

• Devices and software provided
• 1. Prosilica CV640 Machine Vision Camera (CMOS
  technology, IEEE 1394A FireWire connection)
• 2. Laboratory computer with monitor
• 3. National Instruments LabVIEW Graphical
  Development Environment
• 4. National Instruments Advanced IMAQ Vision for
  LabVIEW
• 5. NI-IMAQ IEEE 1394 Machine Vision Support
  Package

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Image Acquisition Module Design Overview (2)
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Image Acquisition Module Design Overview (3)
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Image Acquisition Module Design Overview (4)

• Image capturing

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Image Acquisition Module Design Overview (5)

• Image control
• Prosilica camera driver
• NI IMAQ for IEEE 1394 driver

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Image Acquisition Module Design Overview (6)

• Graphical user interface
• NI LabVIEW and IMAQ develop environment
• Program flow
• GUI operation and functionalities (demo)

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Image Acquisition Module Functionality
Validation

• Confirm camera operations
• Continuous image
• Camera feature controls
• Confirm LabVIEW GUI operations
• Display, save, open, pseudo-colour, and digital
  zoom for still and continuous image
• Additional features

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Image Acquisition Module Performance Analysis
(1)

• Frame Rate
• Test procedure
• Results
• Sample Image Acquisition Module video test
  capture
• Sample consumer camera test capture
• Conclusions drawn

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Image Acquisition Module Performance Analysis
(2)

• Intensity
• Test procedure
• Results
• Rabbit heart specimen Image under microscope 10x
  at half 6V30W
• Top shutter 4095, brightness 255, gain 0
• Bottom shutter 4095, brightness 255, gain
  16
• Conclusion drawn

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Image Acquisition Module Performance Analysis
(3)

• Wavelength
• Test procedure
• Results
• Top Left Multi-wavelength image captured by IAqM
  at Prosilica camera setting of shutter 750,
  gain 0, brightness 0, gamma 0
• Top Right Multi-wavelength image captured by
  KODAK-LS443
• Bottom Quantum efficiency graph of the Prosilica
  CV640 CMOS digital camera
• Conclusion drawn

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Image Acquisition Module Performance Analysis
(4)

• Resolution
• Test procedure
• Results
• Side Rabbit heart cell image captured by IAqM
  via microscope at 10x overall magnification
• Field of view and clarity
• Conclusion drawn

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Image Acquisition Module Next Steps and
Future Improvements

• Overview design for functional prototype
• Hardware performance improvements
• GUI output and control improvements

37
Technical Features of CAPIS
-- Making it the Biomedical Way

• Image Generation Module
• Image Acquisition Module
• Image Analysis Module

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Image Analysis Module Overview

1. Problem Definition Module Goals
2. Module Specifications
3. Our Approach
4. System Design Geodesic Splines
5. System Design MATLAB LWM Transform
6. Test Data Sets
7. Test Results
8. Recommendations for Future Development

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Problem Definition Motion Artifact

• Two types of motion artifact
• Intra-frame blurriness
• Cause undersampling
• Require high frame rate from CCD camera
• Inter-frame variations
• Image changes shape from frame to frame
• Difficult to analyze
• Requires image registration

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Module Goals

• Match input image with base image
• Boundary matching
• Interior stretching
• Preserve gradient

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Module Specifications

• General requirements
• Post-capture processing, done on a per-frame
  basis
• Hardware requirements
• Reasonable processing speed and efficiency
• Input requirements
• 8-bit, grayscale polygons
• Gradient images
• User-defined landmarks
• Performance requirements
• Save and display results

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Our Approach

• Landmark-based image registration
• COTS vs. Customized Research Product
• Therefore, two branches
• Geodesic Splines
• Based on research of Dr. Faisal Beg, Medical
  Image Analysis Lab (MIAL), SFU
• MATLAB (software by The Mathworks, Inc.)
• Using in-the-box image registration capabilities

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Younes and CamionGeodesic Splines Optimisation

• General description
• Minimising energy based on both smoothness and
  data fitting term
• Iterative process called gradient descent
• Implemented by Dr. Faisal Beg

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Block Representation
Windows or Linux
Linux
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Input Parameters
s 4
s 8
s 16

• Are application specific
• Depend on inputs (landmarks) and the goal of the
  matching
• Major Parameters
• e-Energy
• Greens kernel
• ? weighting

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System Design MATLAB Branch

• MATLAB 6 Release 12 application
• Local-weighted mean (LWM) transform
• Command line interface
• Research grade software
• Focus evaluate algorithm performance
• Not as robust as it can be

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System Flow Chart
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Test Data 1 Demonstrative Polygons

• Grayscale, gradient polygons
• Generated in Adobe Photoshop
• Successive transformations
• Simulate shape variations in series of images

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Test Data 2 Fluorescent Heart Images

• Realistic fluorescent rabbit heart images
• Similar to expected input images
• Source Living State Physics, Vanderbilt
  University

www.vanderbilt.edu/lsp/panoraming.htm
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Simulating Quantum Dots

• What are quantum dots (QD)?
• Semiconductor nanocrystals
• Fluorescent labels as landmarks
• Salt noise to simulate QD
• Distinguished labels
• Randomness

Test image
Add noise image to test image
Generate salt noise image

Fluorescence image with QD
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Live Demo
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Demonstrative Polygons Test
Polygon Base
Polygon Input 1
Polygon Input 2
Polygon Input 3
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Demonstrative Polygons Test
MATLAB
All Landmarks
Interior Only
Base
Input1toBase
Input2toBase
Input3toBase
Geodesic Splines
Input1toBase
Input2toBase
Input3toBase
Base
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Demonstrative Polygons Test
All Landmarks
Interior Only
MATLAB
GS
Input3toBase
Input1toBase
Input2toBase
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Demonstrative Polygons Test
Geodesic Spline Input01toBase Input02toBase Input03toBase
Polygons All 98.480 98.466 97.614
Interior 96.904 96.451 96.961

MATLAB Input01toBase Input02toBase Input03toBase
Polygons All 98.171 74.314 72.598
Interior 98.364 74.314 98.042
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Fluorescence Image Test
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Fluorescence Image Test
All Landmarks
Interior Only
MATLAB
Base Image
InputToBase
Input Image
GS
Base Image
InputToBase
Input Image
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Fluorescence Image Test
MATLAB All landmarks
MATLAB Interior points
Geodesic Spline All landmarks
Geodesic Spline Interior points
Geodesic Splines
Fluorescence Image All 84.532 Interior 83.857
MATLAB
Fluorescence Image All 90.571 Interior 77.137
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Current Limitations

• MATLAB Image Registration
• Cumbersome to select landmarks manually
• Some landmarks fade after multiple iteration
• Sensitive to landmark placement
• Geodesic Splines Image Matching
• Computation time
• Operating system constraint (temporary)
• Overall System Scheme
• Non-practical for large sets of images

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MATLAB vs. Geodesic Spline

• Geodesic Spline matching greater accuracy
• MATLAB is faster
• Short-term solution MATLAB
• Long-term solution Geodesic Splines

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Recommendations for Future Development

• Automate/semi-automate landmark selection
• Increase efficiency in landmark-matching tools
• Modify image I/O (e.g. Batch Mode operation)
• Input parameter optimization in geodesic splines
  method
• Automating geodesic splines matching pathway

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Business Component of CAPIS
-- Making it the Biomedical Way
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Business Component CMI Core Business

• 1. Cardiac Action Potential Imaging System
  (CAPIS)
• 2. Customize system to suit the need
• 3. Customize the LabVIEW Interface

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Business Component - Client

• Dr. Glen Tibbits of BC Research Institute of
  Childrens and Womens Health

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Business Component - Statistics

• In British Columbia, 40,000 babies were born
• 600 babies are born with congenital heart disease
• Of that about 200 will require open heart surgery
• 1 in 10 will go into Arrhythmia
• Source Statistics Canada

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Business Component Marketing Strategies

• Short Term
• Research Based Institute
• Children Hospitals and Children Research
  Institute
• Long Term
• Spin off into several groups
• Customize software
• Customize system
• Selling to Research Institutes

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Business Component Proof of Concept

• Research 360.35
• Apparatus
• Company Registration/Administration 512.05
• Total Cost 872.40

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Business Component Product Price for
Proof-of-Concept

• Component Price (CAD)
• 1. USB FireWire cable 41.81
• 2. Heat sink and accessories 18.82
• 3. Bock Electronics (Lens for CCD
  Camera) 186.61
• 4. Lexon blue LED and power supply 68.11
• NET PRODUCT PRICE (after tax) 362.65

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Conclusion
-- Making it the Biomedical Way
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Contact Information

• Website www.sfu.ca/sluu/concardio.html
• Email ensc-bcri_at_sfu.ca
• Phone [phone]
• Address 654-8155 Park Road
• Richmond, British Columbia
• V6Y 1S9

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Q A
-- Making it the Biomedical Way