Project Name

Vendor Independent PA Imaging System Enabled with Asynchronous Laser Source
Last updated: 03/26/2017

Summary

Enter a short narrative description here

  • Student: Yixuan Wu
  • Mentor(s): Haichong Kai Zhang, Emad Boctor

Background, Specific Aims, and Significance

Photoacoustic (PA) imaging is an imaging modality that derives image contrast from the optical absorption coefficient of the tissue being imaged . Owing to its deep penetration, high resolution and safety, it is intensively and widely applied in fundamental, preclinical and clinical studies as a very effective optical imaging modality. However, hardware of PA imaging hinders a universal application of this technology. Implementation either relies on low-efficiency Ultrasound (US) beamformers or vender-variant PA platforms. If conventional US scanner implementing PA imaging is viable, then the cost of PA imaging will be lower so that more life will be saved. Thanks to the effort of Medical UltraSound Imaging and Intervention Collaboration (MUSiiC) Lab, an innovative photoacoustic re-beamforming approach has been developed to make real-time PA implementation on conventional US platforms possible. However, this approach is applied on an ultrasound platform where frame rate and probe’s beamline sweeping rate are manually set. Whereas, conventional clinical ultrasound scanners don’t possess such “triggers” for frames and sweeping. In another word, the phase and frequency of the laser pulse are unknown, leading to a random-looking image where the transmitted signal is asynchronous with the received signal. Hence, a reconstruction method which recovers the laser frequency and the laser phase are significant and crucial for implementing PA imaging on conventional US platform.

Deliverables

  • Minimum: (3/27)
    1. Ultrasound system environment setup.
    2. Simulation in Matlab with k-wave tool box:
      (1) Algorithm to correct frequency error
      (2) Algorithm to correct phase error
  • Expected: (4/20)
    1. Incorporate Matlab code in C++ and transplant it onto Ultrasonix
    2. PZT element tests for verification of the algorithm
  • Maximum: (5/05)
    1. Algorithm improvement: higher accuracy and efficiency
    2. Summary of PA imaging using clinical US scanners in a paper for submission
    3. An in-class demo of PA imaging using clinical US scanners

Technical Approach

To implement PA imaging on US platforms, difference between the two should be well considered and image reconstruction methods for PA imaging are acquired. One critical problem that must be solved before PA imaging can be totally applied onto conventional US scanners is the synchronization. Since conventional US platforms don’t have laser trigger, when does each frame starts (phase of the laser) and when does the frequency of the laser are unknown. The way to solve the problem is to first simulate the whole process in Matlab, with assistance of k-wave tool box. Then transplant the algorithm in C++ onto Ulterius, construct phantoms and validate on clinical ultrasound platforms. One very initial and intuitive though about the algorithm is to set bounds and intervals for Tframe and Tpulse, and search the optimal one by brute-force. Other approaches may include solving optimization problems to get the best image quality. Instead of synchronization, image reconstruction has also to be real-time. This has been achieved by group 13 in Computer Integrated Surgery II 2016. The technical approach here is to combine the real-time imaging part with data obtained after synchronization to make PA imaging on US platform viable.

Dependencies

Software:

  • Matlab k-wave tool box – for PA imaging simulation (Acquired)
  • Visual studio 2010 (Acquired, but may reinstall)
  • QT creator (Acquired)
  • OpenCV 2.4.11 (Acquired)

Hardware:

  • The Ultrasonix SonixTouch US imaging machine
  • US phantom (basic phantoms available)

Milestones and Status

Reports and presentations

Project Bibliography

  1. Ordered List ItemSu, Jimmy L., et al. “Advances in clinical and biomedical applications of photoacoustic imaging.” Expert opinion on medical diagnostics 4.6 (2010): 497-510.
  2. Nikitin, Sergey. Laser ultrasonics in a diamond anvil cell for investigation of simple molecular compunds at ultrahigh pressures. Diss. Université du Maine, 2015.
  3. Bae, Moo-Ho, and Mok-Kun Jeong. “A study of synthetic-aperture imaging with virtual source elements in B-mode ultrasound imaging systems.” IEEE transactions on ultrasonics, ferroelectrics, and frequency control 47.6 (2000): 1510-1519.
  4. Zhang, Haichong K., et al. “Synthetic-aperture based photoacoustic re-beamforming (SPARE) approach using beamformed ultrasound data.” Biomedical Optics Express 7.8 (2016): 3056-3068.
  5. Prince, Jerry L., and Jonathan M. Links. Medical imaging signals and systems. Upper Saddle River, New Jersey: Pearson Prentice Hall, 2006.
  6. Singh, Mithun KA, and Wiendelt Steenbergen. “PhotoAcoustic-guided Focused UltraSound imaging (PAFUSion) for reducing reflection artifacts in photoacoustic imaging.” European Conference on Biomedical Optics. Optical Society of America, 2015.
  7. Muyinatu A. Lediju Bell, lecture notes for Ultrasound and Photoacoustic beamforming
  8. Toennies, Klaus D. Guide to medical image analysis: methods and algorithms. Springer Science & Business Media, 2012.

Other Resources and Project Files

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courses/446/2017/446-2017-02/project.txt · Last modified: 2019/08/07 16:01 (external edit)




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