Digital pathology and telepathology require imaging tools with high-throughput, high-resolution and accurate color reproduction. Lens-free on-chip microscopy based on digital in-line holography is a promising technique towards these needs, as it offers a wide field of view (FOV >20 mm2) and high resolution with a compact, low-cost and portable setup. Color imaging has been previously demonstrated by combining reconstructed images at three discrete wavelengths in the red, green and blue parts of the visible spectrum, i.e., the RGB combination method. However, this RGB combination method is subject to color distortions. To improve the color performance of lens-free microscopy for pathology imaging, here we present a wavelet-based color fusion imaging framework, termed “digital color fusion microscopy” (DCFM), which digitally fuses together a grayscale lens-free microscope image taken at a single wavelength and a low-resolution and low-magnification color-calibrated image taken by a lens-based microscope, which can simply be a mobile phone based cost-effective microscope. We show that the imaging results of an H&E stained breast cancer tissue slide with the DCFM technique come very close to a color-calibrated microscope using a 40x objective lens with 0.75 NA. Quantitative comparison showed 2-fold reduction in the mean color distance using the DCFM method compared to the RGB combination method, while also preserving the high-resolution features of the lens-free microscope. Due to the cost-effective and field-portable nature of both lens-free and mobile-phone microscopy techniques, their combination through the DCFM framework could be useful for digital pathology and telepathology applications, in low-resource and point-of-care settings.
Research laboratories and the industry rely on yeast viability and concentration measurements to adjust fermentation parameters such as pH, temperature, and pressure. Beer-brewing processes as well as biofuel production can especially utilize a cost-effective and portable way of obtaining data on cell viability and concentration. However, current methods of analysis are relatively costly and tedious. Here, we demonstrate a rapid, portable, and cost-effective platform for imaging and measuring viability and concentration of yeast cells. Our platform features a lens-free microscope that weighs 70 g and has dimensions of 12 × 4 × 4 cm. A partially-coherent illumination source (a light-emitting-diode), a band-pass optical filter, and a multimode optical fiber are used to illuminate the sample. The yeast sample is directly placed on a complementary metal-oxide semiconductor (CMOS) image sensor chip, which captures an in-line hologram of the sample over a large field-of-view of >20 mm2. The hologram is transferred to a touch-screen interface, where a trained Support Vector Machine model classifies yeast cells stained with methylene blue as live or dead and measures cell viability as well as concentration. We tested the accuracy of our platform against manual counting of live and dead cells using fluorescent exclusion staining and a bench-top fluorescence microscope. Our regression analysis showed no significant difference between the two methods within a concentration range of 1.4 × 105 to 1.4 × 106 cells/mL. This compact and cost-effective yeast analysis platform will enable automatic quantification of yeast viability and concentration in field settings and resource-limited environments.
Lensfree holographic on-chip imaging is a potent solution for high-resolution and field-portable bright-field imaging over a wide field-of-view. Previous lensfree imaging approaches utilize a pixel super-resolution technique, which relies on sub-pixel lateral displacements between the lensfree diffraction patterns and the image sensor’s pixel-array, to achieve sub-micron resolution under unit magnification using state-of-the-art CMOS imager chips, commonly used in e.g., mobile-phones. Here we report, for the first time, a wavelength scanning based pixel super-resolution technique in lensfree holographic imaging. We developed an iterative super-resolution algorithm, which generates high-resolution reconstructions of the specimen from low-resolution (i.e., under-sampled) diffraction patterns recorded at multiple wavelengths within a narrow spectral range (e.g., 10-30 nm). Compared with lateral shift-based pixel super-resolution, this wavelength scanning approach does not require any physical shifts in the imaging setup, and the resolution improvement is uniform in all directions across the sensor-array. Our wavelength scanning super-resolution approach can also be integrated with multi-height and/or multi-angle on-chip imaging techniques to obtain even higher resolution reconstructions. For example, using wavelength scanning together with multi-angle illumination, we achieved a halfpitch resolution of 250 nm, corresponding to a numerical aperture of 1. In addition to pixel super-resolution, the small scanning steps in wavelength also enable us to robustly unwrap phase, revealing the specimen’s optical path length in our reconstructed images. We believe that this new wavelength scanning based pixel super-resolution approach can provide competitive microscopy solutions for high-resolution and field-portable imaging needs, potentially impacting tele-pathology applications in resource-limited-settings.