Difference between revisions of "Ultrasound acquisition"
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The Phonology Lab has a [http://bkultrasound.com/ultrasonix/systems/sonixtabletq SonixTablet] system from Ultrasonix for performing ultrasound studies. Consult with Susan Lin for permission to use this system. |
The Phonology Lab has a [http://bkultrasound.com/ultrasonix/systems/sonixtabletq SonixTablet] system from Ultrasonix for performing ultrasound studies. Consult with Susan Lin for permission to use this system. |
||
+ | |||
== Data acquisition workflow == |
== Data acquisition workflow == |
||
− | The standard way to acquire ultrasound data is to run an Opensesame experiment on a data acquisition computer that |
+ | The standard way to acquire ultrasound data is to run an Opensesame experiment on a data acquisition computer that controls the SonixTablet and saves timestamped data and metadata for each acquisition. |
=== Prepare the experiment === |
=== Prepare the experiment === |
||
− | The first step is to prepare your experiment. You will need to create an [[ultrasession in opensesame|Opensesame script]] with a series of speaking prompts and data acquisition commands. In simple situations you can simply edit a few variables in our sample script and be ready to go. |
+ | The first step is to prepare your experiment. You will need to create an [[ultrasession in opensesame|Opensesame script]] with a series of speaking prompts and data acquisition commands. In simple situations you can simply edit a few variables in our sample script and be ready to go. Do not start your OpenSesame experiment until after turning the Ultrasonix system on or you risk the system not starting. |
=== Run the experiment === |
=== Run the experiment === |
||
+ | |||
+ | These are the steps you take when you are ready to run your experiment: |
||
+ | |||
+ | ==== Check the audio card ==== |
||
+ | |||
+ | Normally the Steinberg UR22 USB audio interface is used to collect microphone and synchronization signals. |
||
+ | |||
+ | # If the 'USB' light on the front of the UR22 is not solid white, check the USB cable connections at both ends. |
||
+ | # Ensure the UR22 is the default Windows recording device. See the Windows Control Panel > Sound > Recording settings. The 'Steinberg UR22' device (possibly labelled 'Line' rather than 'Microphone') should be marked as the default device and have a green check mark. If it is not the default device, select it and click the 'Set Default' button to change its status. |
||
+ | # Set the +48V switch on the back of the UR22 to 'On'. The '+48V' light on the UR22 should glow solid red. This setting provides phantom power for condenser microphones, which we almost always use in the Lab. |
||
+ | # Plug the microphone into XLR input 1. |
||
+ | # Plug the synchronization signal cable into XLR input 2. |
||
+ | # Check to make sure the 'Mix' knob is turned all the way to 'DAW'. |
||
+ | # Set the gain levels for the microphone and synchronization signals with the 'Input 1' and 'Input 2' knobs. |
||
==== Start the ultrasound system ==== |
==== Start the ultrasound system ==== |
||
+ | # Unplug one of the external monitors' video cables from the splitter that is plugged into the Ultrasonix's external video port. |
||
# Turn on the ultrasound system's power supply, found on the floor beneath the system. |
# Turn on the ultrasound system's power supply, found on the floor beneath the system. |
||
# Turn on the ultrasound system with the pushbutton on the left side of the machine. |
# Turn on the ultrasound system with the pushbutton on the left side of the machine. |
||
+ | # Once Windows has started you can plug the second external monitor's video cable back into the splitter. |
||
# Start the Sonix RP software. |
# Start the Sonix RP software. |
||
+ | # If the software is in fullscreen (clinical) mode, switch to windowed research mode as illustrated in the screenshot. |
||
+ | |||
+ | [[File:research_mode.png]] |
||
==== Start the data acquisition system ==== |
==== Start the data acquisition system ==== |
||
+ | # Turn on the data acquisition computer next to the ultrasound system and use the LingGuest account. |
||
+ | # Check your hardware connections and settings: |
||
+ | ## The Steinberg UR22 USB audio device should be connected to the data acquisition computer. |
||
+ | ## The subject microphone should be connected to 'Mic/Line 1' of the audio device. Use the patch panel if your subject will be in the soundbooth. |
||
+ | ## Make sure the '+48V' switch on the back of the audio device is set to 'On' if you are using a condenser mic (usually recommended). |
||
+ | ## Make a test audio recording of your subject and adjust the audio device's 'Input 1 Gain' setting as needed. |
||
+ | ## The synchronization signal cable should be connected to the BNC connector labelled '25' on the SonixTablet, and the other end should be connected to 'Mic/Line 2' of the audio device. |
||
+ | ## The audio device's 'Input 2 Hi-Z' button should be selected (pressed in). |
||
+ | ## The audio device's 'Input 2 Gain' setting should be at the dial's midpoint. |
||
+ | # Open and run your Opensesame experiment. |
||
− | == |
+ | == Postprocessing == |
+ | Each acquisition resides in its own timestamped directory. If you follow the normal Opensesame script conventions these directories are created in per-subject subdirectories of your base data directory. Normal output includes a <code>.bpr</code> file containing ultrasound image data, a <code>.wav</code> containing speech data and the ultrasound synchronization signal in separate channels, and a <code>.idx.txt</code> file containing the frame indexes of each frame of data in the <code>.bpr</code> file. |
||
− | Early versions of <code>ultracomm</code> and <code>ultrasession.py</code> had issues with occasional hangs when run in an Opensesame experiment. These problems are believed to have been resolved as of the Summer 2015 0.2.1-alpha release of <code>ultracomm</code> when used with an up-to-date <code>ultrasession.py</code> and following the inline scripts used in the sample experiment. Nevertheless, it is good form to check for instances of <code>sox</code> and <code>ultracomm</code> that continue to run after your experiment has concluded, as they may continue to write data to disk until they are terminated. To do this press <code>Ctrl-Alt-Delete</code> and open the Task Manager. Check the Processes tab for instances of <code>sox.exe</code> and <code>ultracomm.exe</code> and use the End Process button to terminate these programs if they are present. |
||
+ | |||
+ | === Getting the code === |
||
+ | |||
+ | Some of the examples in this section make use of [http://github.com/rsprouse/ultratils <code>ultratils</code>] and [http://github.com/rsprouse/audiolabel<code>audiolabel</code>] Python packages from within the [[Berkeley Phonetics Machine]] environment. Other examples are shown in the Windows environment as it exists on the Phonology Lab's data acquisition machine. To keep up-to-date with the code in the BPM, open a Terminal window in the virtual machine and give these commands: |
||
+ | |||
+ | sudo bpm-update bpm-update |
||
+ | sudo bpm-update ultratils |
||
+ | sudo bpm-update audiolabel |
||
+ | |||
+ | Note that the <code>audiolabel</code> package distributed in the current BPM image (2015-spring) is not recent enough for working with ultrasound data, and it needs to be updated. <code>ultratils</code> is not in the current BPM image at all. |
||
+ | |||
+ | === Synchronizing audio and ultrasound images === |
||
+ | |||
+ | The first task in postprocessing is to find the synchronization pulses in the <code>.wav</code> file and relate them to the frame indexes in the <code>.idx.txt</code> file. You can do this with the <code>psync</code> script, which you can call on the data acquisition workstation like this: |
||
+ | |||
+ | python C:\Anaconda\Scripts\psync --seek <datadir> # Windows environment |
||
+ | psync --seek <datadir> # BPM environment |
||
+ | |||
+ | Where <datadir> is your data acquisition directory (or a per-subject subdirectory if you prefer). When invoked with <code>--seek</code>, <code>psync</code> finds all acquisitions that need postprocessing and creates corresponding <code>.sync.txt</code> and <code>.sync.TextGrid</code> files. These files contain time-aligned pulse indexes and frame indexes in columnar and Praat textgrid formats, respectively. Here 'pulse index' refers to the synchronization pulse that is sent for every frame acquired by the SonixTablet; 'frame index' refers to the frame of image data actually received by the data acquisition workstation. Ideally these indexes would always be the same, but at high frame rates the SonixTablet cannot send data fast enough, and some frames are never received by the data acquisition machine. These missing frames are not present in the <code>.bpr</code> file and have 'NA' in the frame index (encoded on the 'raw_data_idx' tier) of the <code>psync</code> output files. For frames that are present in the <code>.bpr</code> you use the synchronization output files to find their corresponding times in the audio file. |
||
+ | |||
+ | === Separating audio channels === |
||
+ | |||
+ | If you wish you can also separate the audio channels of the <code>.wav</code> file into <code>.ch1.wav</code> and <code>.ch2.wav</code> with the <code>sepchan</code> script: |
||
+ | |||
+ | python C:\Anaconda\Scripts\sepchan --seek <datadir> # Windows environment |
||
+ | sepchan --seek <datadir> # BPM environment |
||
+ | |||
+ | This step takes a little longer than <code>psync</code> and is optional. |
||
+ | |||
+ | === Extracting image data === |
||
+ | |||
+ | You can extract image data with Python utilities. In this example we will extract an image at a particular point in time. |
||
+ | First, load some packages: |
||
+ | |||
+ | from ultratils.pysonix.bprreader import BprReader |
||
+ | import audiolabel |
||
+ | import numpy as np |
||
+ | |||
+ | <code>BprReader</code> is used to read frames from a <code>.bpr</code> file, and <code>audiolabel</code> is used to read from a <code>.sync.TextGrid</code> synchronization textgrid that is the output from <code>psync</code>. |
||
+ | |||
+ | Open a <code>.bpr</code> and a <code>.sync.TextGrid</code> file for reading with: |
||
+ | |||
+ | bpr = '/path/to/somefile.bpr' |
||
+ | tg = '/path/to/somefile.sync.TextGrid' |
||
+ | rdr = BprReader(bpr) |
||
+ | lm = audiolabel.LabelManager(from_file=tg, from_type='praat') |
||
+ | |||
+ | For convenience we create a reference to the 'raw_data_idx' textgrid label tier. This tier provides the proper time alignments for image frames as they occur in the <code>.bpr</code> file. |
||
+ | |||
+ | bprtier = lm.tier('raw_data_idx') |
||
+ | |||
+ | Next we attempt to extract the index label for a particular point in time. We enclose this part in a <code>try</code> block to handle missing frames. |
||
+ | |||
+ | timept = 0.485 |
||
+ | data = None |
||
+ | try: |
||
+ | bpridx = int(bprtier.label_at(timept).text) # ValueError if label == 'NA' |
||
+ | data = rdr.get_frame(int(bpridx)) |
||
+ | except ValueError: |
||
+ | print "No bpr data for time {:1.4f}.".format(timept) |
||
+ | |||
+ | Recall that some frames might be missed during acquisition and are not present in the <code>.bpr</code> file. These time intervals are labelled 'NA' in the 'raw_data_idx' tier, and attempting to convert this label to <code>int</code> results in a ValueError. What this means is that <code>data</code> will be <code>None</code> for missing image frames. If the label of our timepoint was not 'NA', then image data will be available in the form of a numpy ndarray in <code>data</code>. This is a rectangular array containing a single vector for each scanline. |
||
+ | |||
+ | === Transforming image data === |
||
+ | |||
+ | Raw <code>.bpr</code> data is in rectangular format. This can be useful for analysis, but is not the norm for display purposes since it does not account for the curvature of the transducer. You can use the <code>ultratils</code> <code>Converter</code> and <code>Probe</code> objects to transform into the expected display. To do this, first load the libraries: |
||
+ | |||
+ | from ultratils.pysonix.scanconvert import Converter |
||
+ | from ultratils.pysonix.probe import Probe |
||
+ | |||
+ | Instantiate a <code>Probe</code> object and use it along with the header information from the <code>.bpr</code> file to create a <code>Converter</code> object: |
||
+ | |||
+ | probe = Probe(19) # Prosonic C9-5/10 |
||
+ | converter = Converter(rdr.header, probe) |
||
+ | |||
+ | We use the probe id number 19 to instantiate the <code>Probe</code> object since it corresponds to the Prosonic C9-5/10 in use in the Phonology Lab. (Probe id numbers are defined by Ultrasonix in <code>probes.xml</code> in their SDK, and [https://github.com/rsprouse/ultratils/blob/master/ultratils/pysonix/data/probes.xml a copy of this file] is in the <code>ultratils</code> repository.) The <code>Converter</code> object calculates how to transform input image data, as defined in the <code>.bpr</code> header, into an output image that takes into account the transducer geometry. Use <code>as_bmp()</code> to perform this transformation: |
||
+ | |||
+ | bmp = converter.as_bmp(data) |
||
+ | |||
+ | Once a <code>Converter</code> object is instantiated it can be reused for as many images as desired, as long as the input image data is of the same shape and was acquired using the same probe geometry. All the frames in a <code>.bpr</code> file, for example, satisfy these conditions, and a single <code>Converter</code> instance can be used to transform any frame image from the file. |
||
+ | |||
+ | These images illustrate the transformation of the rectangular <code>.bpr</code> data into a display image. |
||
+ | |||
+ | [[File:bpr.png|400px]] [[File:bmp.png|400px]] |
||
+ | |||
+ | If the resulting images are not in the desired orientation you can use <code>numpy</code> functions to flip the data matrix: |
||
+ | |||
+ | data = np.fliplr(data) # Flip left-right. |
||
+ | data = np.flipud(data) # Flip up-down. |
||
+ | bmp = converter.as_bmp(data) # Image will be flipped left-right and up-down. |
||
+ | |||
+ | === In development === |
||
+ | |||
+ | Additional postprocessing utilities are under development. Most of these are in the [https://github.com/rsprouse/ultratils <code>ultratils</code> github repository]. |
||
+ | |||
+ | == Troubleshooting == |
||
+ | See the [[ultrasonix troubleshooting|Ultrasonix troubleshooting page]] page to correct known issues with the Ultrasonix system. |
||
− | A known issue is that the ultrasound system sometimes starts imaging but never sends data to the acquisition computer. This situation occurs in about 1% of acquisitions and results in empty <code>.bpr</code> and <code>.bpr.idx.txt</code> files. |
Latest revision as of 12:28, 25 June 2018
The Phonology Lab has a SonixTablet system from Ultrasonix for performing ultrasound studies. Consult with Susan Lin for permission to use this system.
Data acquisition workflow
The standard way to acquire ultrasound data is to run an Opensesame experiment on a data acquisition computer that controls the SonixTablet and saves timestamped data and metadata for each acquisition.
Prepare the experiment
The first step is to prepare your experiment. You will need to create an Opensesame script with a series of speaking prompts and data acquisition commands. In simple situations you can simply edit a few variables in our sample script and be ready to go. Do not start your OpenSesame experiment until after turning the Ultrasonix system on or you risk the system not starting.
Run the experiment
These are the steps you take when you are ready to run your experiment:
Check the audio card
Normally the Steinberg UR22 USB audio interface is used to collect microphone and synchronization signals.
- If the 'USB' light on the front of the UR22 is not solid white, check the USB cable connections at both ends.
- Ensure the UR22 is the default Windows recording device. See the Windows Control Panel > Sound > Recording settings. The 'Steinberg UR22' device (possibly labelled 'Line' rather than 'Microphone') should be marked as the default device and have a green check mark. If it is not the default device, select it and click the 'Set Default' button to change its status.
- Set the +48V switch on the back of the UR22 to 'On'. The '+48V' light on the UR22 should glow solid red. This setting provides phantom power for condenser microphones, which we almost always use in the Lab.
- Plug the microphone into XLR input 1.
- Plug the synchronization signal cable into XLR input 2.
- Check to make sure the 'Mix' knob is turned all the way to 'DAW'.
- Set the gain levels for the microphone and synchronization signals with the 'Input 1' and 'Input 2' knobs.
Start the ultrasound system
- Unplug one of the external monitors' video cables from the splitter that is plugged into the Ultrasonix's external video port.
- Turn on the ultrasound system's power supply, found on the floor beneath the system.
- Turn on the ultrasound system with the pushbutton on the left side of the machine.
- Once Windows has started you can plug the second external monitor's video cable back into the splitter.
- Start the Sonix RP software.
- If the software is in fullscreen (clinical) mode, switch to windowed research mode as illustrated in the screenshot.
Start the data acquisition system
- Turn on the data acquisition computer next to the ultrasound system and use the LingGuest account.
- Check your hardware connections and settings:
- The Steinberg UR22 USB audio device should be connected to the data acquisition computer.
- The subject microphone should be connected to 'Mic/Line 1' of the audio device. Use the patch panel if your subject will be in the soundbooth.
- Make sure the '+48V' switch on the back of the audio device is set to 'On' if you are using a condenser mic (usually recommended).
- Make a test audio recording of your subject and adjust the audio device's 'Input 1 Gain' setting as needed.
- The synchronization signal cable should be connected to the BNC connector labelled '25' on the SonixTablet, and the other end should be connected to 'Mic/Line 2' of the audio device.
- The audio device's 'Input 2 Hi-Z' button should be selected (pressed in).
- The audio device's 'Input 2 Gain' setting should be at the dial's midpoint.
- Open and run your Opensesame experiment.
Postprocessing
Each acquisition resides in its own timestamped directory. If you follow the normal Opensesame script conventions these directories are created in per-subject subdirectories of your base data directory. Normal output includes a .bpr
file containing ultrasound image data, a .wav
containing speech data and the ultrasound synchronization signal in separate channels, and a .idx.txt
file containing the frame indexes of each frame of data in the .bpr
file.
Getting the code
Some of the examples in this section make use of ultratils
and audiolabel
Python packages from within the Berkeley Phonetics Machine environment. Other examples are shown in the Windows environment as it exists on the Phonology Lab's data acquisition machine. To keep up-to-date with the code in the BPM, open a Terminal window in the virtual machine and give these commands:
sudo bpm-update bpm-update sudo bpm-update ultratils sudo bpm-update audiolabel
Note that the audiolabel
package distributed in the current BPM image (2015-spring) is not recent enough for working with ultrasound data, and it needs to be updated. ultratils
is not in the current BPM image at all.
Synchronizing audio and ultrasound images
The first task in postprocessing is to find the synchronization pulses in the .wav
file and relate them to the frame indexes in the .idx.txt
file. You can do this with the psync
script, which you can call on the data acquisition workstation like this:
python C:\Anaconda\Scripts\psync --seek <datadir> # Windows environment psync --seek <datadir> # BPM environment
Where <datadir> is your data acquisition directory (or a per-subject subdirectory if you prefer). When invoked with --seek
, psync
finds all acquisitions that need postprocessing and creates corresponding .sync.txt
and .sync.TextGrid
files. These files contain time-aligned pulse indexes and frame indexes in columnar and Praat textgrid formats, respectively. Here 'pulse index' refers to the synchronization pulse that is sent for every frame acquired by the SonixTablet; 'frame index' refers to the frame of image data actually received by the data acquisition workstation. Ideally these indexes would always be the same, but at high frame rates the SonixTablet cannot send data fast enough, and some frames are never received by the data acquisition machine. These missing frames are not present in the .bpr
file and have 'NA' in the frame index (encoded on the 'raw_data_idx' tier) of the psync
output files. For frames that are present in the .bpr
you use the synchronization output files to find their corresponding times in the audio file.
Separating audio channels
If you wish you can also separate the audio channels of the .wav
file into .ch1.wav
and .ch2.wav
with the sepchan
script:
python C:\Anaconda\Scripts\sepchan --seek <datadir> # Windows environment sepchan --seek <datadir> # BPM environment
This step takes a little longer than psync
and is optional.
Extracting image data
You can extract image data with Python utilities. In this example we will extract an image at a particular point in time. First, load some packages:
from ultratils.pysonix.bprreader import BprReader import audiolabel import numpy as np
BprReader
is used to read frames from a .bpr
file, and audiolabel
is used to read from a .sync.TextGrid
synchronization textgrid that is the output from psync
.
Open a .bpr
and a .sync.TextGrid
file for reading with:
bpr = '/path/to/somefile.bpr' tg = '/path/to/somefile.sync.TextGrid' rdr = BprReader(bpr) lm = audiolabel.LabelManager(from_file=tg, from_type='praat')
For convenience we create a reference to the 'raw_data_idx' textgrid label tier. This tier provides the proper time alignments for image frames as they occur in the .bpr
file.
bprtier = lm.tier('raw_data_idx')
Next we attempt to extract the index label for a particular point in time. We enclose this part in a try
block to handle missing frames.
timept = 0.485 data = None try: bpridx = int(bprtier.label_at(timept).text) # ValueError if label == 'NA' data = rdr.get_frame(int(bpridx)) except ValueError: print "No bpr data for time {:1.4f}.".format(timept)
Recall that some frames might be missed during acquisition and are not present in the .bpr
file. These time intervals are labelled 'NA' in the 'raw_data_idx' tier, and attempting to convert this label to int
results in a ValueError. What this means is that data
will be None
for missing image frames. If the label of our timepoint was not 'NA', then image data will be available in the form of a numpy ndarray in data
. This is a rectangular array containing a single vector for each scanline.
Transforming image data
Raw .bpr
data is in rectangular format. This can be useful for analysis, but is not the norm for display purposes since it does not account for the curvature of the transducer. You can use the ultratils
Converter
and Probe
objects to transform into the expected display. To do this, first load the libraries:
from ultratils.pysonix.scanconvert import Converter from ultratils.pysonix.probe import Probe
Instantiate a Probe
object and use it along with the header information from the .bpr
file to create a Converter
object:
probe = Probe(19) # Prosonic C9-5/10 converter = Converter(rdr.header, probe)
We use the probe id number 19 to instantiate the Probe
object since it corresponds to the Prosonic C9-5/10 in use in the Phonology Lab. (Probe id numbers are defined by Ultrasonix in probes.xml
in their SDK, and a copy of this file is in the ultratils
repository.) The Converter
object calculates how to transform input image data, as defined in the .bpr
header, into an output image that takes into account the transducer geometry. Use as_bmp()
to perform this transformation:
bmp = converter.as_bmp(data)
Once a Converter
object is instantiated it can be reused for as many images as desired, as long as the input image data is of the same shape and was acquired using the same probe geometry. All the frames in a .bpr
file, for example, satisfy these conditions, and a single Converter
instance can be used to transform any frame image from the file.
These images illustrate the transformation of the rectangular .bpr
data into a display image.
If the resulting images are not in the desired orientation you can use numpy
functions to flip the data matrix:
data = np.fliplr(data) # Flip left-right. data = np.flipud(data) # Flip up-down. bmp = converter.as_bmp(data) # Image will be flipped left-right and up-down.
In development
Additional postprocessing utilities are under development. Most of these are in the ultratils
github repository.
Troubleshooting
See the Ultrasonix troubleshooting page page to correct known issues with the Ultrasonix system.