This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $423,151 to Duke University to develop a new functional brain imaging technology using super-resolution ultrasound. The goal is to create a radiation-free, low-cost system that can noninvasively map deep-brain neural activities at high spatiotemporal resolution. The research aims to overcome limitations of current brain imaging technologies by leveraging deep learning and ultrafast...
This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award of $200,000 to Oakland University aims to develop a novel low-cost, wireless 3D ultrasound imaging system for use in low-resource settings. The key goals are to: 1) establish quantitative tools using signal processing and artificial intelligence to extract ultrasound-derived biomarkers for improved breast cancer diagnosis, and 2) develop a robust calibration, registration, and sensor fusion protocol to...
This Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $183,980 to support research on the theoretical and algorithmic foundations of novel medical imaging modalities at the University of Arizona. The research aims to advance the underlying mathematics and image reconstruction algorithms for emerging modalities like photoacoustic tomography, magnetoacoustoelectric tomography, and ultrasound current density imaging....
The National Science Foundation Office of Advanced Cyberinfrastructure awarded the University of Texas at Austin a $1.2 million Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) from September 1, 2022 to August 31, 2025. The grant funds research to develop a rigorous and reliable scientific deep learning framework for forward, inverse, and uncertainty quantification problems in computational science and engineering. Specific objectives include...
The National Science Foundation (NSF) awarded a $406,900 Project Grant under the Engineering (CFDA 47.041) program to Texas A&M Engineering Experiment Station (Tees) to develop large-scale optical ultrasound transducer (OUT) arrays for high-speed and high-resolution 3D acoustic tomography. The project aims to create a new optical technology that can detect and convert acoustic wave fields into optical signals, enabling improved performance and reduced cost for 3D ultrasound imaging...
This $840,292 Project Grant awarded by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program aims to develop a transformative three-dimensional (3D) ultrasound imaging technology that can democratize access to advanced ultrasound imaging capabilities. The research objective is to overcome technical challenges and knowledge gaps to enable the conversion of existing two-dimensional (2D) ultrasound systems into 3D-capable devices, thereby...
This National Science Foundation (NSF) Project Grant award under the Engineering program (CFDA 47.041) provides $199,930 to the University of Chicago to assess microbubble-induced stresses on soft materials like tissue, in order to support the development of regulatory guidelines for bubble-based medical devices like therapeutic ultrasound systems. The key objectives are to: 1) develop and characterize a mechanophore-based tissue phantom to quantify microbubble-induced deformation, 2)...
This $300,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports fundamental research on inverse boundary value problems and related mathematical techniques. The key research areas include: Electrical impedance tomography (EIT) for determining the conductivity of materials by making voltage and current measurements at the boundary. The research will address challenges in EIT such as partial data, anisotropic...
The National Science Foundation Office of Integrative Activities awarded a $231,682 Project Grant to the University of Alabama under the Integrative Activities federal grant program (CFDA 47.083) to develop an aberration-free computational framework for transcranial photoacoustic computed tomography (PACT) brain imaging. Over the two year period from January 2023 to December 2024, a faculty fellow and graduate student will work with experts at the University of Illinois Urbana-Champaign to...
This four-year, $1.1 million Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund the development of physics-informed machine learning techniques to analyze dynamic blood flow from static subtraction computed tomographic angiography imaging. The University of Wisconsin-Milwaukee will train graduate students in deep learning methods and engage undergraduates and local high school students, particularly those from...
The National Science Foundation awarded a $200,000 Project Grant to the University of Chicago under the Engineering (47.041) federal grant program. The grant will support the creation of two open-source, high-performance computing-enabled deep learning frameworks to significantly improve the reconstruction speed and quality of full waveform inversion-based ultrasound computed tomography. One framework will incorporate adjoint tomography theory into a generative adversarial network to accelerate full waveform inversion reconstruction for rapid patient screening. The second will leverage physics-guided, cycle-consistency in both training and application to provide detailed reconstruction while reducing reliance on ground truth models and initial assumptions. Both aim to lower false positives and negatives to enable earlier diagnosis and treatment. Additional outcomes include disseminating computational methods, studying scientific problems associated with the techniques, and establishing an associated cyberinfrastructure and clinically relevant databases. The award period is from Aug 1, 2022 to Jul 31, 2025.