Biomedical optics express最新文献

3D super-resolution fluorescence microscopy typically requires sophisticated setups, sample preparation, or long measurements. A notable exception, SOFI, only requires recording a sequence of frames and no hardware modifications whatsoever but being a wide-field method, it faces problems in thick, dense samples. We combine SOFI with temporal focusing two-photon excitation - the wide-field method that is capable of exciting a thin slice in 3D volume. Temporal focusing is simple to implement whenever the excitation path of the microscope can be accessed. The implementation of SOFI is straightforward. By merging these two methods, we obtain super-resolved 3D images of neurons stained with quantum dots. Our approach offers reduced bleaching of out-of-focus fluorescent probes and an improved signal-to-background ratio that can be used when robust resolution improvement is required in thick, dense samples.

Proximal rotary scanning is predominantly used in the clinical practice of endoscopic and intravascular OCT, mainly because of the much lower manufacturing cost of the probe compared to distal scanning. However, proximal scanning causes severe beam stability issues (also known as non-uniform rotational distortion, NURD), which hinders the extension of its applications to functional imaging, such as OCT elastography (OCE). In this work, we demonstrate the abilities of learning-based NURD correction methods to enable the imaging stability required for intensity-based OCE. Compared with the previous learning-based NURD correction methods that use pseudo distortion vectors for model training, we propose a method to extract real distortion vectors from a specific endoscopic OCT system, and validate its superiority in accuracy under both convolutional-neural-network- and transformer-based learning architectures. We further verify its effectiveness in elastography calculations (digital image correlation and optical flow) and the advantages of our method over other NURD correction methods. Using the air pressure of a balloon catheter as a mechanical stimulus, our proximal-scanning endoscopic OCE could effectively differentiate between areas of varying stiffness of atherosclerotic vascular phantoms. Compared with the existing endoscopic OCE methods that measure only in the radial direction, our method could achieve 2D displacement/strain distribution in both radial and circumferential directions.

Time-domain diffuse correlation spectroscopy (td-DCS) enables the depth discrimination in tissue's blood flow recovery, considering the fraction of photons detected with higher time of flight (TOF) and longer pathlength through the tissue. However, the recovery result depends on factors such as the instrument response function (IRF), analyzed TOF gate start time, gate width and the source-detector separation (SDS). In this research we evaluate the performance of the td-DCS technique at three SDSs of 1.5, 2 and 2.5 cm to recover cerebral blood flow (CBF). To do that we presented comprehensive characterization of the td-DCS system through a series of phantom experiments. First by quality metrices such as coefficient of variation and contrast-to-noise ratios, we identified optimal time gate(s) of the TOF to extract dynamics of particles. Then using sensitivity metrices, each SDS ability to detect dynamics of particles in superficial and deeper layer was evaluated. Finally, td-DCS at each SDS was tested on healthy volunteers during cuff occlusion test and breathing tasks. According to phantom measurements, the sensitivity to estimate perfusion within the deep layer located at depth of 1.5 cm from the surface can be increased more than two times when the SDS increases from 1.5 cm to 2.5 cm.