Empowering Low-Cost CMOS Cameras by Image Processing to Reach Comparable Results with Costly CCDs

Abstract

Despite the hugeresearch effort to improve the performanceoftheComplementaryMetalOxideSemiconductor (CMOS) image sensors, Charge-Coupled Devices (CCDs) still dominate the cell biology related conventional fluorescence microscopic imaging market where low or ultra-low noise imaging is required. A detailed comparison of the sensor specifications and performance is usually not provided by the manufacturers which leads the end users not to go out of the habitude and choose a CCD camera instead of a CMOS one. However, depending on the application, CMOS cameras, when empowered by image processing algorithms can become cost-efficient solutions for conventional fluorescence microscopy. In this paper, we introduce an application-based comparative study between the default CCD camera of an inverted microscope (Nikon Ti-S Eclipse) and a custom-designed CMOS camera and apply efficient image processing algorithms to improve the performance of CMOS cameras. Quantum micro-bead samples that emit fluorescence light at different intensity levels, breast cancer diagnostic tissue cell and Caco-2 cell samples are imaged by both CMOS and CCD cameras and results are provided to show the reliability of CMOS camera processed images and finally to be of assistance when scientists select their cameras for desired applications.

Quantitative estimation of biological cell surface receptors by segmenting conventional fluorescence microscopy images

“…In a similar fashion, other Caco-2 cell samples were also exposed to LPS, then stained using immunofluorescence. The images were acquired using a CMOS image sensor which is able to replace CCD sensors for a range of bio-monitoring applications, including TLR monitoring [6]. The acquired images were processed using three different image segmentation schemes, which are proven to be able to localize and segment such biomarkers [7].…”