UCLA researchers have developed a compressive sampling algorithm for on-chip fluorescent imaging over an ultra-large field-of-view without the need for any lenses or mechanical scanning.
Fluorescent imaging has become quite powerful, with various applications in biomedical sciences, ranging from high-throughput screening to sorting and characterization of cells. Rare cell analysis is a big challenge in the fluorescent imaging field. The concentration of the target cell (e.g., a circulating tumor cell) is extremely low with a density of less than a few hundred per mL. One solution to this challenging task involves the use of large-area micro-fluidic devices (e.g., with an active area of >9 cm2) to enable screening of a large volume of sample (e.g., whole blood) to capture adequate number of target cells within the device volume. However, imaging field-of-view (FOV) for conventional objective-lens based fluorescent microscopes is typically <2-3 mm2. This mismatch between the active-area of the microfluidic device and the FOV of the microscope-objective necessitates the capture of multiple images while scanning the sample. Compressive sampling aims to recover a function (i.e., a signal) from many fewer measurements/samples than normally required according to Shannon’s sampling theorem. This emerging theory has been recently applied to various fields to bring new insights to measurement and imaging science.
UCLA inventors have developed a compressive sampling algorithm for on-chip fluorescent imaging over an ultra-large field-of-view without the need for any lenses or mechanical scanning. The fluorescent samples placed on a chip are excited through a prism interface, where the pump light is filtered out by total internal reflection after exciting the entire sample volume. The emitted fluorescent light from the specimen is collected through an on-chip fiber-optic faceplate and is delivered to a wide field-of-view optoelectronic sensor array for lensless recording of the fluorescent spots corresponding to the samples. A compressive sampling based optimization algorithm is then used to rapidly reconstruct the sparse distribution of fluorescent sources to achieve ~10 μm spatial resolution over the entire active region of the sensor-array, i.e., over an imaging field-of-view of >8 cm2.
|United States Of America||Issued Patent||9,331,113||05/03/2016||2010-595|