Excitation modalities for enhanced micro and nanoparticle imaging in a smartphone coupled 3D printed fluorescent microscope

Abstract

Smartphone fluorescent microscopes (SFM) offer many functional characteristics similar to their benchtop counterparts at a fraction of the cost and have been shown to work for biomarker detection in many...

AQAFI: a bioanalytical method for automated KPIs quantification of fluorescent images of human leukocytes and micro–nano particles

“…The choice of smartphone and the external lens used for creating magnification immensely affect the SFM performance and in its current configuration, the presented SFM has a measured optical resolution of about 2.2 μm. 21 Simply measuring the optical resolution alone is not enough, we need to have more quantifiable metrics to compare the final imaging performances of different SFM designs and configurations so that we can get a better understanding of their performance limitations and work toward improving them.…”

“…† A detailed protocol outlining the methodology employed to identify these optimal ranges can be found in our previous study. 21…”

“…18 Previously, our group has been involved in research focusing on designing multiple smartphone fluorescence microscopes. [19][20][21] The initial version of our SFM design was capable of working with multiple fluorophores, offered compatibility with multiple modern smartphones, and just like its benchtop counterparts, offered the user multiple magnification levels. 20 Furthermore, in order to automate the counting of particles imaged using our SFM, we also worked on the development of a particle quantification algorithm using deep convolutional neural networks.…”

“…21 It was at this point that we realized that in addition to imaging smaller and smaller fluorescent particles, we also need a metric to quantifiably assess the quality of the fluorescent images captured using a particular SFM design. 21 To do so, we picked two success metrics, the signal difference to noise ratio (SDNR) and contrast to noise ratio (CNR). [24][25][26][27] These metrics are calculated on the basis of bead intensity, bead vicinity intensity, and the background noise in the cap-tured image as shown in Fig.…”

“…We then quantified the imaging performance of the SFM design variants on the basis of these two parameters and found the best performing design. 21 The SDNR and CNR parameters for a fluorescent image captured using SFM were calculated manually by using ImageJ. Though this manual processing gave us a reasonably good estimate of the performance of different SFM variants, it is a very resource and time-intensive method and also only considers a portion of the captured images for SDNR and CNR calculations.…”