Color-sensing image sensor with embedded microfluidics and related methods

Abstract

A color-sensing image sensor with embedded microfluidics includes a silicon substrate having (a) at least one recess partially defining at least one embedded microfluidic channel and (b) a plurality of photosensitive regions for generating electronic signals for position sensing , in response to the light from the at least one concave portion, wherein the at least two photosensitive areas are respectively located in at least two mutually different depth ranges relative to the at least one concave portion to provide color information. A wafer-scale manufacturing method for fabricating multiple such color-sensing image sensors. A method for producing a color image of a fluid sample, comprising performing imaging of the fluid sample deposited in a microfluidic channel embedded in a silicon substrate, to a plurality of photosensitive areas of the silicon substrate, and generating color images based on the depth of light penetration into the silicon substrate Color message.

Description

technical field [0001] The present invention relates to the field of optics, and more particularly to color-sensing image sensors with embedded microfluidics and related methods. Background technique [0002] The results of biological or chemical tests are often determined by using optical imaging methods. Interpretation of assay data based on fluorescence or chemiluminescence imaging is replacing more traditional methods such as gel electrophoresis, non-image-based flow cytometry and mass spectrometry. Fluorescence and chemiluminescence imaging are particularly well-suited for multitasking (composite) inspection data interpretation, because color and spatial positional information is distinguishable between different types of sample components or procedures. [0003] Diagnostic instruments based on the basis of modern optical imaging utilize digital image sensors such as Charge Coupled Device (CCD) sensors or Complementary Metal Oxide Semiconductor (CMOS) image sensors. W...

AI Technical Summary

Problems solved by technology

However, such imaging systems still typically cost several thousand dollars, which reduces market acceptance

Additionally, systems used in point-of-care and / or resource-poor environments must be rugged, maintenance-free, and operable with minimally trained staff, making it particularly challenging to meet cost requirements

For these reasons, many point-of-care and / or low-resource settings rely on laminar flow biosensor assay data interpretation, resulting in poor quantification (if any), limited multitasking (if any) capabilities, and subjective readouts

As a result, patients in such settings are less than optimally treated

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