Application of compressed imaging methods in optics has led to advancements in high-speed snapshot imaging such as Light Field Tomography (LIFT). LIFT utilizes computed tomography and light field imaging to compress a snapshot 3-D field of view into a 1-D line of light. It can achieve excellent imaging speeds when used with a high-speed linear sensor. We propose using LIFT to image multi-neuron dynamics with the ASAP voltage indicator, which has proven challenging to image due to millisecond dynamics and low brightness. Here we report a prototype system to confirm performance by imaging high speed GCaMP Calcium Indicator dynamics.
Cameras with extreme speeds are enabling technologies in both fundamental and applied sciences. However, existing ultrafast cameras are incapable of coping with extended three-dimensional scenes. To address this unmet need, we developed a new category of computational ultrafast imaging technique, light field tomography (LIFT), which can perform three-dimensional snapshot transient (time-resolved) imaging at an unprecedented frame rate with full-fledged light field imaging capabilities including depth retrieval, post-capture refocusing, and extended depth of field. We demonstrated the proof of concept through light-in-flight imaging of a helical-shaped diffused fiber. The advantage of such recordings is that even visually simple systems can be scientifically interesting when they are captured three-dimensionally at such a high speed. The ability to film the propagation of light through a curved optical path, for example, could inform the design of invisibility cloaks and other optical metamaterials.
Significance: Coherence, a fundamental property of waves and fields, plays a key role in photoacoustic image reconstruction. Previously, techniques such as short-lag spatial coherence (SLSC) and filtered delay, multiply, and sum (FDMAS) have utilized spatial coherence to improve the reconstructed resolution and contrast with respect to delay-and-sum (DAS). While SLSC uses spatial coherence directly as the imaging contrast, FDMAS employs spatial coherence implicitly. Despite being more robust against noise, both techniques have their own drawbacks: SLSC does not preserve a relative signal magnitude, and FDMAS shows a reduced contrast-to-noise ratio.
Aim: To overcome these limitations, our aim is to develop a beamforming algorithm—generalized spatial coherence (GSC)—that unifies SLSC and FDMAS into a single equation and outperforms both beamformers.
Approach: We demonstrated the application of GSC in photoacoustic computed tomography (PACT) through simulation and experiments and compared it to previous beamformers: DAS, FDMAS, and SLSC.
Results: GSC outperforms the imaging metrics of previous state-of-the-art coherence-based beamformers in both simulation and experiments.
Conclusions: GSC is an innovative reconstruction algorithm for PACT, which combines the strengths of FDMAS and SLSC expanding PACT’s applications.
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