Plane-Wave Imaging Challenge in Medical Ultrasound
Summary (1 min read)
Description of the datasets
- PICMUS has been designed for PWI and CPWC beamforming techniques.
- Two datasets were generated with Field II [4, 5].
- A second simulated dataset included a number of anechoic cysts, also distributed vertically and horizontally, over fully developed speckle .
- Besides, a collection of MATLAB classes were provided to the participants specifying how to interact with the datasets, together with a reference implementation of delay-and-sum (DAS) beamforming.
- Figure 1 Schematic of the upper part of the CIRS Model 040GSE Phantom used for the experiments.
Description of the metrics
- Contrast and resolution are, by far, the most used metrics to assess image quality.
- The FWHM obtained for all scatterers in the image were averaged to obtain the average axial and lateral resolution in both simulations and experiments .
- The speckle quality test was considered positive, if the tested regions obtained a significance level α = 0.05 in the KS test.
- Description of the competition and the ranking Research challenges are inherently competitive.
- Four categories have been set depending on the number of plane-wave selected by the participants Category I: 1 plane-waves, Category II: 11 plane-waves, Category III: 75 plane-waves, Category IV: arbitrary number of plane-waves.
- All the information is available at the website https://www.creatis.insa-lyon.fr/Challenge/IEEE_IUS_2016/.
- It describes the datasets, the metrics, provides a link to the data and the code, as well as some more general information about the organization of the challenge.
- Other transmit strategies could also be interesting topics for a challenge, like for example synthetic aperture imaging.
- Also PICMUS does not take into account the processing time, which might be decisive in the assessment of the methods applicability.
- The authors believe utterly important to maintain the platform in time, open for other users to use and contribute, supporting the objective intercomparison of methods and promoting fruitful discussion on the relevance of new ideas.
- The authors would like to thank Verasonics who supported the challenge financially and particularly Mike Vega.
- Special thanks to Peter Krakovski for his advice on data acquisition.
- The authors would also like to thank the IEEE IUS organization committee and technical program committee as well as all members of the ultrasound community who supported this effort.
- This work was performed within the framework of the Labex PRIMES (ANR-10-LABX-0063) of Université de Lyon, within the program "Investissements d'Avenir" (ANR-11IDEX-0007) operated by the French Nation-al Research Agency (ANR).
- Part of this work was also supported by the Center for Innovative Ultrasound Solutions for health care, maritime, and oil & gas, CIUS which is a Norwegian Research Council appointed centre for research-based innovation.
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Cites methods from "Plane-Wave Imaging Challenge in Med..."
...In the ultrasound community, a recent attempt to address this issue was made with the PICMUS challenge  (Tours, IUS 2016)....
...The code downloads a CPWC dataset from the PICMUS challenge , beamforms it, and displays it....
Cites background or methods from "Plane-Wave Imaging Challenge in Med..."
...We thank the PICMUS organizers, including Prof. Jørgen A. Jensen from the Technical University of Denmark; Dr. Alfonso Rodriguez-Molares from the Norwegian University of Science and Technology; Prof. Hervé Liebgott, Dr. Frederic Cervenansky, and Dr. Oliver Bernard from the University of Lyon for sharing imaging data and the code for coherent compounding....
...beamformers are demonstrated on a series of data sets acquired using a research scanner ....
...We apply the beamformers to experimental data acquired by scanning a multipurpose tissue-mimicking phantom (model 040GSE, CIRS, Norfolk, VA, USA) ....
...We demonstrate the beamformers on imaging data provided by the Plane-wave Imaging Challenge in Medical Ultrasound (PICMUS) ....
...by the plane-wave imaging challenge in medical ultrasound (PICMUS) ....
"Plane-Wave Imaging Challenge in Med..." refers methods in this paper
...Two datasets were generated with Field II [4, 5]....
"Plane-Wave Imaging Challenge in Med..." refers background in this paper
...The challenge includes: a website with all available information, the challenge platform (MIDAS), two simulated CPWC datasets in HDF5 format, two experimental CPWC datasets in HDF5 format, example code, in MATLAB, on how to interact with the datasets, and tests for contrast, resolution, geometrical distortion, and speckle appearance....
...PICMUS has been designed for PWI and CPWC beamforming techniques....
...However, this drawback was skilfully addressed by Coherent Plane-Wave Compounding (CPWC) , which introduced a trade-off between framerate and image quality....
"Plane-Wave Imaging Challenge in Med..." refers methods in this paper
...This was already the objective with synthetic aperture imaging (STA) ....
...Note that compounding is also used in STA. Beamforming has therefore regained a lot of its past attention, with the proposal of numerous beamforming techniques that aim to increase image quality without losing framerate....
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Frequently Asked Questions (10)
Q1. What have the authors contributed in "Plane-wave imaging challenge in medical ultrasound" ?
PICMUS, the Plane-Wave Imaging Challenge in Medical Ultrasound aims to provide these tools. This paper describes the PICMUS challenge, its motivation, implementation, and metrics.
Q2. What was the reason for the penalization of methods that removed speckle?
Considering that speckle is an intrinsic characteristic of ultrasound images, it was decided to penalize methods that removed speckle.
Q3. What is the purpose of the challenge?
The authors believe utterly important to maintain the platform in time, open for other users to use and contribute, supporting theobjective intercomparison of methods and promoting fruitful discussion on the relevance of new ideas.
Q4. What was the penalty for the scatterers?
Geometrical distortion was penalyzed if the maximum distance of any scatterer from its theoretical position was greater than one wavelength.
Q5. What is important when motion is considered?
When motion is considered not only the number of transmitted angles is important, but also the order in which they have been transmitted.
Q6. What is the intention of the organisers to maintain the platform?
It is the intention of the organisers to maintain the platform as long as possible and even keep extending it in the future to support comparison with other methods after the challenge.
Q7. What is the name of the center?
Part of this work was also supported by the Center for Innovative Ultrasound Solutions for health care, maritime, and oil & gas, CIUS which is a Norwegian Research Council appointed centre for research-based innovation.
Q8. What are the main reasons why the challenge is organized?
Challenges are regularly organized and hosted by medical imaging conferences like IEEE International Symposium on Biomedical Imaging [http://biomedicalimaging.org/2016/] or Medical Image Computing and Computer Assisted Intervention MICCAI [http://www.miccai2016.org/en/].
Q9. What was the CNR for the anechoic cysts?
Contrast was estimated with the classical expression for contrast to noise ratio (CNR),10 2 2 20log / 2 in outin outCNR (1)where μin and μout are the mean gray level inside and outside the anechoic cystic region, and in and out are the gray level standard deviation inside and outside the anechoic cystic region.
Q10. What was the purpose of the experiment?
The participants were then asked to beamform the four datasets on a specific grid of points, and to supply the envelope image before any kind of compression.