Data-driven Solutions for Extremely Ill-posed Tomographic Imaging — NSF Award to Michigan State University (MI, $400,000)
Computational imaging, particularly involving radiography and tomography, has a critical role in a variety of industries including security systems, materials science, non-destructive testing, seismic imaging, and medical imaging. Current methods for generating images rely on conventional physical models or on AI-based
| Award title | Data-driven Solutions for Extremely Ill-posed Tomographic Imaging |
|---|---|
| Award ID | 2436945 |
| Awardee | Michigan State University |
| City | EAST LANSING |
| State | MI |
| Amount obligated | $400,000 |
| Principal investigator | Saiprasad Ravishankar |
| Program | CSCS: Circuits and Systems for |
| Start date | 09/01/2025 |
| Abstract | Computational imaging, particularly involving radiography and tomography, has a critical role in a variety of industries including security systems, materials science, non-destructive testing, seismic imaging, and medical imaging. Current methods for generating images rely on conventional physical models or on AI-based models that learn patterns in data. These current methods are limited in applications with lower quality data, or where the patterns in the data are highly complex, or where the c |
| Source | NSF Awards |
$799/mo
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