Local conditional neural fields for versatile and generalizable large-scale reconstructions in computational imaging
Deep learning has transformed computational imaging, but traditional pixel-based
representations limit their ability to capture continuous, multiscale details of objects. Here we …
representations limit their ability to capture continuous, multiscale details of objects. Here we …
RED-PSM: Regularization by denoising of partially separable models for dynamic imaging
B Iskender, ML Klasky… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Dynamic imaging involves the recovery of a time-varying 2D or 3D object at each time
instant using its undersampled measurements. In particular, in dynamic tomography, only a …
instant using its undersampled measurements. In particular, in dynamic tomography, only a …
Automated three-dimensional image registration for longitudinal photoacoustic imaging
B De Santi, L Kim, RFG Bulthuis… - … of biomedical optics, 2024 - spiedigitallibrary.org
Significance Photoacoustic tomography (PAT) has great potential in monitoring disease
progression and treatment response in breast cancer. However, due to variations in breast …
progression and treatment response in breast cancer. However, due to variations in breast …
Spatiotemporal image reconstruction to enable high-frame-rate dynamic photoacoustic tomography with rotating-gantry volumetric imagers
Significance Dynamic photoacoustic computed tomography (PACT) is a valuable imaging
technique for monitoring physiological processes. However, current dynamic PACT imaging …
technique for monitoring physiological processes. However, current dynamic PACT imaging …
RED-PSM: Regularization by Denoising of Factorized Low Rank Models for Dynamic Imaging
Dynamic imaging addresses the recovery of a time-varying 2D or 3D object at each time
instant using its undersampled measurements. In particular, in the case of dynamic …
instant using its undersampled measurements. In particular, in the case of dynamic …