Dr. Muyinatu Bell and gynecologic surgeon collaborator Dr. Karen Wang were among the 30 interdisciplinary faculty teams at Johns Hopkins selected to receive one of the 2018 JHU Discovery Awards. This award is designed to support cross-divisional research teams who are poised to arrive at important discoveries or creative works. The expectation is that these awards will spark new, synergistic interactions between investigators across the institution and lead to work of the highest quality and impact. This award will support their research topic of “Photoacoustic Image Guidance of Gynecological Surgeries.”
Prof. Bell is one of “100 outstanding early career engineers” selected to meet for an intensive 2-1/2 day symposium to discuss cutting-edge developments in four engineering areas at the National Academy of Engineering’s 2018 US Frontiers of Engineering Symposium. This symposium will be hosted by MIT Lincoln Laboratory in Lexington, Massachusetts, September 5-7, 2018.
Effective May 1, 2018, Prof. Bell will receive a secondary appointment as an Assistant Professor in the Department of Computer Science at JHU.
Congratulations to Derek Allman! His paper entitled “Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning” was accepted to the IEEE Transactions on Medical Imaging. This paper is expected to appear in the Special Issue on Machine Learning for Image Reconstruction.
This work is the first to use deep convolutional neural networks (CNNs) as an alternative to the photoacoustic beamforming and image reconstruction process. We used simulations to train CNNs to identify sources and reflection artifacts in raw photoacoustic channel data, reformatted the network outputs to usable images that we call CNN-Based images, and transferred these trained networks to operate on experimental data. Multiple parameters were varied during training (e.g., channel noise, number of sources, number of artifacts, sound speed, signal amplitude, transducer model, lateral and axial locations of sources and artifacts, and spacing between sources and artifacts). The classification accuracy of simulation and experimental data ranged from 96-100% when the channel signal-to-noise ratio was -9 dB or greater and when sources were located in trained locations. Over 99% of the results had submillimeter location accuracy. Our CNN-Based images have high contrast, no artifacts, and resolution that rivals the traditional photoacoustic image resolution of low-frequency ultrasound probes.
Citation: D Allman, A Reiter, MAL Bell, Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning, IEEE Transactions on Medical Imaging (accepted) [pdf]
Congratulations to Arun Nair on the acceptance of his manuscript to the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Paper ID: 3434
Title: A DEEP LEARNING BASED ALTERNATIVE TO BEAMFORMING ULTRASOUND IMAGES
Session Title: ‘SAM Poster Session 4: Beamforming’
Authors: AA Nair, T Tran, A Reiter, MAL Bell
This conference will take place 15–20 April 2018.
Congratulations to Prof. Bell for being selected to receive the NSF CAREER Award. The Faculty Early Career Development (CAREER) Program is a Foundation-wide activity that offers the National Science Foundation’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. The objective of Prof. Bell’s proposal entitled CAREER: Technical & Theoretical Foundations for Photoacoustic-Guided Surgery is to apply optical analyses, spatial coherence theory, and independent resolution models to describe fundamental performance limits of photoacoustic-based navigation during robotic and nonrobotic surgery.
Congrats to undergraduate student Margaret Allard on the acceptance of her first-author journal paper entitled Feasibility of photoacoustic-guided teleoperated hysterectomies. This paper will appear in the Journal of Medical Imaging (JMI) Special Section on Image-Guided Procedures, Robotic Interventions, and Modeling.
This paper is the first to describe the feasibility of photoacoustic integration with the da Vinci surgical robot to potentially guide minimally invasive hysterectomies and other gynecological surgeries. To implement photoacoustic imaging, a novel light delivery system was designed and implemented to surround da Vinci tools. This new light delivery system uniquely enabled the investigations described in the paper, including the first known analysis of the optimal tool orientations for photoacoustic-guided hysterectomies using a da Vinci scissor tool (which partially blocks the transmitted light in some cases). This work can be extended to other da Vinci tools and laparoscopic instruments with similar tip geometry.
Margaret completed this work through her participation in our NSF Research Experience for Undergraduates in Computational Sensing and Medical Robotics.
Congratulations to PULSE Lab undergraduate student Brooke Stephanian on her 2nd place win in the Optics and Photonics Conference at JHU! She presented a poster that summarized the work she completed this semester on the topic “Theoretical Simulation to Optimize Short-Lag Spatial Coherence (SLSC) Photoacoustic Image Quality”.
Conference website: https://engineering.jhu.edu/ece/osa/hopkins-photonics-conference/
Congrats to Arun Nair on the acceptance of his paper entitled “Robust Short-Lag Spatial Coherence Imaging” to the IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. This paper will appear in the special issue on sparsity driven methods in medical ultrasound.
This work is the first to re-examine the lag summation step of the Short-Lag Spatial Coherence (SLSC) algorithm and achieve additional robustness to coherence outliers through both weighted summation of individual coherence images (i.e., M-weighting) and the application of robust principal component analysis (i.e., Robust SLSC, or R-SLSC). Results show great promise for smoothing out the tissue texture of SLSC images, improving boundary delineation, and enhancing anechoic or hypoechoic target visibility at higher lag values. These improvements could be useful in clinical tasks such as breast cyst visualization, liver vessel tracking, and obese patient imaging.
Citation: AA Nair, T Tran, MAL Bell, Robust Short-Lag Spatial Coherence Imaging, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (accepted) [pdf]
Also Available on Journal Website: http://ieeexplore.ieee.org/document/8166807/
Congrats to undergraduate student Brooke Stephanian and PhD student Derek Allman! Their abstracts were accepted to the 2017 Optics and Photonics Conference at Johns Hopkins University.
Brooke will present a poster entitled: Theoretical Simulation to Optimize Short-Lag Spatial Coherence (SLSC) Photoacoustic Image Quality
Derek will give a presentation entitled: Using convolutional neural networks to eliminate reflection artifacts in experimental photoacoustic images
Conference details: https://engineering.jhu.edu/ece/osa/hopkins-photonics-conference/
Our paper, “Feasibility of photoacoustic guided hysterectomies with the da Vinci robot,” was accepted for Oral presentation at SPIE Medical Imaging in the Image-Guided Procedures, Robotic Interventions, and Modeling conference.
Keynote and Medical Robotics
Tuesday 13 February 2018
10:10 AM – 12:10 PM
Feasibility of photoacoustic guided hysterectomies with the da Vinci robot
Authors: Margaret Allard, Joshua Shubert, Muyinatu A. Lediju Bell
Congrats to Margaret, Josh, and Prof. Bell!
Three PULSE Lab abstracts were accepted to SPIE Photonics West in the BiOS Conference Track: Photons Plus Ultrasound: Imaging and Sensing 2018 (Conference 10494). This conference track will take place Sunday- Wednesday January -28-31, 2018 at the The Moscone Center in San Francisco, California.
- A novel drill design for photoacoustic guided surgeries
Authors: Joshua Shubert, Muyinatu BellSession 3: Therapy Monitoring and Guidance IISunday 28 January 2018
1:30 PM – 2:45 PM
- Using convolutional neural networks to eliminate reflection artifacts in experimental photoacoustic images
Authors: Derek Allman, Austin Reiter, Muyinatu Bell
Session PTue: Posters-Tuesday
Tuesday 30 January 2018
6:00 PM – 8:00 PM
- Development and validation of a short-lag spatial coherence theory for photoacoustic imaging
Authors: Michelle Graham, Muyinatu Bell
Session PTue: Posters-Tuesday
Tuesday 30 January 2018
6:00 PM – 8:00 PM
Congrats to Josh, Derek, and Michelle!
Conference track website: https://spie.org/PWB/conferencedetails/photons-plus-ultrasound
Congrats to Joshua Shubert on passing his ECE Department Qualifying Exam!
Congrats to Derek Allman and Michelle Graham on passing their ECE Department Qualifying Exams!
The UltraSound Toolbox (USTB) is a free MATLAB toolbox for processing ultrasonic signals. The primary purpose of the USTB is to facilitate the comparison of imaging techniques and the dissemination of research results. The PULSE Lab is proud to collaborate on this effort to deliver SLSC beamforming to the broader ultrasound community. An example using the SLSC algorithm on a CIRS phantom and on human heart data was added today, as described here: http://www.ustb.no/examples/advanced-beamforming/short-lag-spatial-coherence-slsc/. The heart and phantom datasets and the SLSC code are now freely available to use. Additional datasets and beamforming code can be found by perusing the USTB website.
Congrats to Ole Marius Hoel Rindal (our visiting student from the University of Oslo) for putting in the work required to pull this together!
Congratulations to PULSE Lab undergraduate student Margaret Allard who received the best presentation award from the NSF REU program in Computational Sensing and Medical Robotics. Her presentation was entitled Identifying Optimal da Vinci Tool Orientations for Photoacoustic Guided Hysterectomies. Prof. Jerry Prince presented Margaret with this award.
This award was shared by Margaret Allard and Mindy Wagenmaker.
Our paper entitled Photoacoustic-based approach to surgical guidance performed with and without a da Vinci robot was accepted for publication in the Journal of Biomedical Optics (JBO) Special Section on Translational Biophotonics.
Congrats to undergraduates Neeraj Gandhi and Margaret Allard!
This work was completed in partnership with the NSF REU in Computational Sensing and Medical Robotics along with collaborators Sungmin Kim and Peter Kazanzides, and it is the first to integrate photoacoustic imaging with the da Vinci surgical robot. It was also featured on the journal homepage.
Three PULSE Lab abstracts were accepted for presentation during the 2017 IEEE International Ultrasonics Symposium (IUS) to be held on September 6-9, 2017 at the Omni Shoreham Hotel, Washington D.C., USA.
- “Theoretical Application of Short-Lag Spatial Coherence to Photoacoustic Imaging” to be presented by Michelle Graham in the MBB: Non linear and coherence imaging poster session, 3-4 pm on Thursday, September 7, 2017. (Abstract ID: 1526)
- “Photoacoustic Visual Servoing of Needle Tips to Improve Biopsy Targeting in Obese Patients” to be presented by Joshua Shubert in the MPA: Technical Developments in Photoacoustic Imaging poster session, 3-4 pm on Friday, September 8, 2017. (Abstract ID: 1088)
- “Identification and removal of reflection artifacts in photoacoustic images using convolutional neural networks” to be presented by Derek Allman in the MIM: Machine learning poster session, 9:30-10:30 am on Saturday, September 9, 2017. (Abstract ID: 1523)
Congrats to Michelle, Josh, and Derek!
Symposium website: http://ewh.ieee.org/conf/ius/2017/
Congratulations to Blackberrie Eddins on the acceptance of her manuscript, Design of a Multifiber Light Delivery System for Photoacoustic-Guided Surgery, for publication in the Journal of Biomedical Optics to appear in the 2017 Photoacoustic Imaging and Sensing Special Section.
Congratulations to PULSE Lab undergraduate student Blackberrie Eddins for winning the first place final presentation award in the 2016 NSF Computational Sensing and Medical Robotics (CSMR) Research Experience for Undergraduates (REU) program at JHU! She tied in first place for this award with Luke Arend, another student participant.