A unique deep learning network, Deep-E, is proposed, which utilizes 2D training data to solve a 3D problem. The novelty of this simulation method is to generate a 2D matrix in the axial-elevational plane using an arc-shaped transducer element, instead of generating a 3D matrix using the linear transducer arrays. Deep-E exhibited significant resolution improvement on the in vivo human breast data. In addition, we were able to restore deeper vascular structures and remove the noise artifact. We envision that Deep-E will have a significant impact in linear-array-based photoacoustic imaging studies by providing high-speed and high-resolution image enhancement.
This study analyzes the light emission pattern of tapered optical fibers (TFs) across different numerical apertures (NA), core diameters, laser input powers, cone angles, and light injection angles. The results will be used to tailor optical fibers for optimal light delivery to photosensitive neuronal actuators in the non-human primate (NHP) brain.
Light emission at 1.54 μm from an Er-doped amorphous silicon nitride layer coupled to photonic crystal resonators
and plamonic arrays is studied. We observe the cavity resonances at cryogenic and room temperatures and under
varying optical pump powers. The results demonstrate that small mode volume, high quality factor resonators
enhance Er absorption rates dramatically at the cavity resonance. Photonic crystal cavity resonances exhibit
linewidth narrowing with pump power at cryogenic temperatures, signifying absorption bleaching and partial
inversion of the Er ions. In addition, we fabricate periodic metal-insulator-metal plasmonic structures with a
simple bottom-up fabrication technique. We observe a factor of 10 increase of Er emission coupled to plasmonic
structures.
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