BMED4962ECSE4962 Introduction to Subsurface Imaging Systems

1
BMED-4962/ECSE-4962Introduction to Subsurface
Imaging Systems

• Lecture 12 Ultrasound scanner as a linear
  system
• Kai E. Thomenius1 Badri Roysam2
• 1Chief Technologist, Imaging Technologies,
• General Electric Global Research Center
• 2Professor, Rensselaer Polytechnic Institute

Center for Sub-Surface Imaging Sensing
2
Outline of Course Topics

• THE BIG PICTURE
• What is subsurface sensing imaging?
• Why a course on this topic?
• EXAMPLE THROUGH TRANSMISSION SENSING
• X-Ray Imaging
• Computer Tomography
• COMMON FUNDAMENTALS
• propagation of waves
• interaction of waves with targets of interest 

• PULSE ECHO METHODS
• Examples
• Multi-dimensional imaging
• MRI
• A different sensing modality from the others
• Basics of MRI
• MOLECULAR IMAGING
• What is it?
• PET Radionuclide Imaging
• IMAGE PROCESSING CAD

3
Recap of Last Lecture

• We have been introduced to the Field II
  simulation program and walked through some of the
  code.
• We have used this Field II example to demonstrate
  the role of linear system theory in the
  understanding of imagers.
• Our goal was to learn about ultrasound scanners
  as well as the tools we use to understand
  design such systems.

4
Linear Systems

• A linear system is completely characterized by
  its impulse response.
• All the processing steps of an ultrasound scanner
  can be modeled as a set of impulse responses.
• Luckily, all these steps have been incorporated
  in a software package called Field II

5
Ultrasound Scanner as a Linear System
Propagation Path (1/2 of calc_hhp)
Transmit Array (xdc_concave, Xdc_impulse)
Pulser (excitation)
Scattering
Propagation Path (1/2 of calc_hhp)
Receive Array (xdc_concave, Xdc_impulse)
Display code

• Each block in this system is covered by an
  impulse response or a transfer function.
• As a consequence, the response of the entire
  system can be modeled as a convolution of the
  impulse responses or the product of the transfer
  functions.

6
Code Review

• Last time we went through the logo code fairly
  quickly.
• Let us finish the last two parts of the code with
  a bit more care.

7
From Last Class Code Review

• Call to xdc_concave
• Purpose Procedure for creating a concave
  transducer
• Calling Th xdc concave (radius, focal radius,
  ele size)
• Input
• Radius Radius of physical elements.
• focal radius Focal radius.
• ele size Size of mathematical elements.
• Output Th - A pointer to this transducer
  aperture.
• Define transducer impulse response
• Hanning-weighted sine wave
• Define the transmit pulse
• Excitation sine wave

• Define the transducer
• Th xdc_concave (R, Rfocus, ele_size)
• Set the impulse response and excitation of the
  emit aperture
• impulse_responsesin(2pif0(01/fs2/f0))
• impulse_responseimpulse_response.hanning(max(siz
  e(impulse_response)))'
• xdc_impulse (Th, impulse_response)
• excitationsin(2pif0(01/fs2/f0))
• xdc_excitation (Th, excitation)
• Calculate the pulse echo field and display it
• xpoints(-100.210)
• RF_data, start_time calc_hhp (Th, Th,
  xpoints zeros(1,101) 30ones(1,101)'/1000)

8
Code Review PSF Determination

• Call to calc_hhp
• Purpose Procedure for calculating the pulse echo
  field.
• Calling hhp, start time calc hhp(Th1, Th2,
  points)
• Input
• Th1 Pointer to the transmit aperture.
• Th2 Pointer to the receive aperture.
• points Field points. Vector with three columns
  (x,y,z) and one row for each field point.
• Output
• RF_data - Received voltage trace.
• start time - The time for the first sample in
  RF_data.

• Calculate the pulse echo field and display it
• xpoints(-100.210)
• RF_data, start_time calc_hhp (Th, Th,
  xpoints zeros(1,101) 30ones(1,101)'/1000)
• Make a display of the envelope
• figure(1)
• envabs(hilbert(RF_data(15600,)))
• env20log10(env/max(max(env)))
• N,Msize(env)
• env(env60).(envgt-60) - 60
• mesh(xpoints, ((0N-1)/fs start_time)1e6, env)
• ylabel('Time \mus')
• xlabel('Lateral distance mm')
• title('Pulse-echo field from 8 mm concave
  transducer at 30 mm')
• axis(-10 10 38.41 39.6 -60 0)
• view(-14 80)

9
Code Review PSF Display

• The highlighted lines perform the following steps
  to create the display
• hilbert is a matlab command which gives the
  envelope of an RF signal
• 20log10() converts the envelope to decibels
• mesh is a matlab command for displaying 2D data

• Calculate the pulse echo field and display it
• xpoints(-100.210)
• RF_data, start_time calc_hhp (Th, Th,
  xpoints zeros(1,101) 30ones(1,101)'/1000)
• Make a display of the envelope
• figure(1)
• envabs(hilbert(RF_data(15600,)))
• env20log10(env/max(max(env)))
• N,Msize(env)
• env(env60).(envgt-60) - 60
• mesh(xpoints, ((0N-1)/fs start_time)1e6, env)
• ylabel('Time \mus')
• xlabel('Lateral distance mm')
• title('Pulse-echo field from 8 mm concave
  transducer at 30 mm')
• axis(-10 10 38.41 39.6 -60 0)
• view(-14 80)

Field II is a very convenient tool that minimizes
the work required to simulate any coherent
scanner.
10
Goal of the Simulation Point Spread Function
for Transducer

• We wish to determine the pulse-echo point spread
  function for this transducer.
• What is that?
• A point spread function (PSF) describes the
  response of an imaging system to a point source
  or point object.
• A related but more general term for the PSF is a
  system's impulse response.
• It can be used to characterize any imaging
  system.

PSF of a confocal microscope convolution with
two targets and resulting image.
11
PSF from a Concave Source
How would you get the point spread function of a
CT scanner?
12
Optics Airy Disc PSF
http//www.optics.arizona.edu/jcwyant/Optics505(20
00)/ChapterNotes/Chapter15/psfandmtfcurves.pdf
13
So, what is a tool like Field II good for?

• Here are a couple of examples

14
Analysis of a complex transmit signal
Regulatory Limits on Transmit Energy Determines
Penetration
Pulse Amplitude
Mechanical Index Limit
Pulse Length
Longer pulse gains penetration but sacrifices
resolution
15
Resolution / Penetration Dilemma
7 MHz
5 MHz
Penetration limited due to Beers Law
16
Possible Solution Coded Excitation
Alternate encodings could use a chirp.
Transmitted Pulse Train
Body

• Sensitivity Increase

Received Pulse Train
1 1 0 1 0 1 1 1
Decoder
Coded Excitation improves sensitivity without
resolution tradeoff
17
The Matched Filter

• Basic Idea
• Suppose you have a signal s(t) with a known
  shape corrupted by additive noise n(t).
• We can construct a matched filter m(t) that is
  designed to maximize our ability to detect s(t)
• The matched filter is only a function of the
  transmitted signals shape (hence the name)
• Its impulse response is a time reversed copy of
  s(t) with some scaling factor a that depends upon
  the noise

Indicates complex conjugate
18
Decoding

• Decoding is done with matched or correlation
  filtering.
• This is often implemented as a convolution.
• Let us assume we transmit a code p(t) and receive
  signal s(t).
• Matched filter can be implemented as the
  convolution of the received signal by the
  time-reversed transmit pulse.

Hardware is readily available to implement
convolution based filtering.
19
How could we evaluate this with Field II?

• Encoding step
• We need to define an excitation function to
  represent the coded signal.
• This can be applied thru the xdc_excitation
  function.
• Decoding step
• Implement the matched filter step in matlab.
• Apply the resulting signal exactly the same way
  as any RF echo.
• The rest of the processing is identical to any of
  the imaging examples given.

20
Coded Excitation - Experiment
High Frequency
Coded Excitation
15 cm
18 cm
Improve penetration by 3 cm with same resolution
to -50 dB
21
Utility of Tools like Field II

• Here are some other applications
• Design tools
• Evaluate an array design without building it.
• Evaluate signal processing techniques
• Use the phantoms to compare detectability of use
  defined lesions
• Teach image formation techniques
• Field II is the most commonly used design tool
  for medical ultrasound.

22
Current Ultrasound Battlefields

• Another area which saw heavy use of Field II was
  3D/4D ultrasound.
• Next couple of slides show some of the key steps
  in getting there.

23
3D/4D Imaging

• In CT, we learned about helical/spiral CT
  acquisition
• This meant getting 3D data.
• So what is 4D Imaging?
• Time is the fourth dimension!

24
2D 3D 4D
3D imaging in real-time
25
Real-Time 3D

• 3D imaging
• Need to move acoustic beams in 3-space
• Mechanical
• Electronic
• Multi-planar, real-time display
• longitudinal, transversal and horizontal planes
• Volume or surface rendered 3D image sets
• Volume rate (as opposed to the frame rate)
  becomes key

3D Voxel
2D Pixel
26
Real-time 3D Beamformation
27
Fully connected 50 50 array
28
Mechanical 4D Solution
Transducer
Cable Drive
Fluid-FilledHousing
Stepper Motor
Belt Drive
Cable
Optimized for high-speedmotion, up to 18 vol/sec
29
Mechanical Probe Images

• Move a 1D array back and forth rapidly over a
  sector.
• Volume rates in the order of 15 25 volumes/sec
  possible.

30
One Possible Solution

• Migrate beamformer components to probe handle.
• With multi-row probes, multiplexing is in the
  handle.
• Patent by Larson from 1993
• group 2D array elements into subarrays
• combine echoes from subarrays and send summed
  signals
• cable count reduced w. reasonable spatial
  sampling.
• Look for more system changes along these lines

Probe Handle
31
Migration of Beamformation to Handle
Modular Beamformerin Probe Handle
2D Transducer Array(vs. human hair)
32
Sub-Array Beamformer in Probe

• Connects a group of transducer elements to each
  system channel
• Low-power analog beamformer Phase rotation or
  Delay lines
• Small delays only static steering of small
  sub-aperture
• Dynamic focusing full-aperture delays by system
  beamformer

33
3D / 4D Applications

• Obstetrics
• Womens Health
• Virtual Hysteroscopy
• Coronal pelvic views
• 3D Breast Imaging
• Musculoskeletal
• Pediatrics
• Urology
• Entire organ scans

New useful applications emerging with 3D/4D
34
New Topic Imaging Motion

• Doppler described the theory of detecting motions
  of stars in his original paper in 1842
• On the colored light of the double stars and
  certain other stars of the heavens.
• Statement of the Doppler Principle
• any directional motion between a light source and
  an observer will produce a detectable frequency
  shift or color change

• Johan Christian Doppler
• born in 1803 in Salzburg, died in 1853 in Venice.
• A Professor of mathematics
• Modern astrophysics is based on his famous
  principle of 1842.

35
What is the Doppler Principle ?

• Doppler described the theory of detecting motions
  of stars in his original paper in 1842
• On the colored light of the double stars and
  certain other stars of the heavens.
• Statement of the Doppler Principle
• any directional motion between a light source and
  an observer will produce a detectable frequency
  shift or color change

36
Doppler Shift Experiment

• In 1845, Christian Doppler did an experiment
• He hired a freight train and the trumpet section
  of the Vienna Orchestra
• Half of the players got on the train and played
  an Eb.
• The other half did the same on the station
• The difference in the pitches was apparent to all
  concerned
• Consider proposing an experiment like this to the
  NIH today...

kenbeta.tripod.com/ thelinkex/
37
Analysis of Experiment

• As the train passed the observers
• the note being played by the musicians on the
  train increased and, after passing the listeners,
  decreased by 1/2 note.
• Observers on the train experienced the same
  effect from the horns at track side.
• Doppler's theory was now verified.

towards
away
38
The Doppler effect is effectively changing the
wavelength of sound at the observer in this
case, keeping the sound velocity the same
39
The Doppler effect is effectively changing the
frequency of sound at the observer in this case,
keeping the wavelength the same
40
(No Transcript)
41
Summary

• We reviewed 3D/4D ultrasound imaging methods
• Linear system simulators like Field II can help
  test prototype design ideas
• Matched filtering can improve SNR
• We introduced the Doppler principle

42
Instructor Contact Information

• Badri Roysam
• Professor of Electrical, Computer, Systems
  Engineering
• Office JEC 7010
• Rensselaer Polytechnic Institute
• 110, 8th Street, Troy, New York 12180
• Phone [phone]
• Fax [phone]
• Email roysam_at_ecse.rpi.edu
• Website http//www.ecse.rpi.edu/roysabm
• Secretary Laraine Michaelides, JEC 7012, (518)
  276 8525, michal_at_rpi.edu

43
Instructor Contact Information

• Kai E Thomenius
• Chief Technologist, Ultrasound Biomedical
• Office KW-C300A
• GE Global Research
• Imaging Technologies
• Niskayuna, New York 12309
• Phone [phone]
• Fax [phone]
• Email thomeniu_at_crd.ge.com, thomenius_at_ecse.rpi.edu
  
• Secretary Laraine Michaelides, JEC 7012, (518)
  276 8525, michal_at_rpi.edu