Super-Resolution Diffusive Optical Imaging

Multiresolution Localization With Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence

“…We assumed a fixed and known fluorescence lifetime for all reporters. While this may be appropriate for some applications, if there should be variations in lifetime because of the local (chemical) environment, lifetime could be estimated along with position, in a revised interpretation of the cost function in (16).…”

“…The weight of each basis function is then estimated by finding the maximum inner products between the measured data y and the dictionary basis functions. For (16), the basis function weight would be η k . However, if high temporal and spatial resolution is desired, as is the case in this work, forming the dictionary and calculating the inner products becomes computationally difficult, which we show in Section IV-B.…”

“…Thus, we assume that the data within the temporal window w comes from a single fluorophore at r f k . A simplified cost function based on (16) can then be written as…”

“…We let N x M P and N z M P be the number of grid points along the x and z dimensions for matching pursuit, where N x M P and N z M P must be very large in order to achieve high spatial resolution. To minimize (16), matching pursuit must calculate O(N x M P N z M P N) inner products since t max = N T , and each inner product involves O(QM N) multiply-add operations. Therefore, the expected run time of matching pursuit is O(QM N x M P N z M P N 2 K ).…”

“…We present a super-resolution localization imaging method that is an extension of earlier localization concepts [10], [16] and is based on spatiotemporal data. There has been substantial prior work done on imaging using a diffusion forward model, but without the point emitter constraint.…”