Fusion of lens-free microscopy and mobile-phone microscopy images for high-color-accuracy and high-resolution pathology imaging

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.

[1]  Yibo Zhang,et al.  Wide-field pathology imaging using on-chip microscopy , 2015, Virchows Archiv.

[2]  Alexander Wilkie,et al.  Novel color printer characterization model , 2003, J. Electronic Imaging.

[3]  Yibo Zhang,et al.  Demosaiced pixel super-resolution for multiplexed holographic color imaging , 2016, Scientific Reports.

[4]  Po-chieh Hung,et al.  Colorimetric calibration for scanners and media , 1991, Electronic Imaging.

[5]  Derek Tseng,et al.  Lensfree microscopy on a cellphone. , 2010, Lab on a chip.

[6]  Henry R. Kang,et al.  Neural network applications to the color scanner and printer calibrations , 1992, J. Electronic Imaging.

[7]  Derek K. Tseng,et al.  Imaging and sizing of single DNA molecules on a mobile phone. , 2014, ACS nano.

[8]  Danny Pascale,et al.  A Review of RGB Color Spaces , 2003 .

[9]  Hongying Zhu,et al.  Cost-effective and compact wide-field fluorescent imaging on a cell-phone. , 2011, Lab on a chip.

[10]  Patrick Jackman,et al.  Robust colour calibration of an imaging system using a colour space transform and advanced regression modelling. , 2012, Meat science.

[11]  Raja Bala,et al.  Two-dimensional transforms for device color correction and calibration , 2005, IEEE Transactions on Image Processing.

[12]  Aydogan Ozcan,et al.  Field-Portable Pixel Super-Resolution Colour Microscope , 2013, PloS one.

[13]  A. Ozcan,et al.  Synthetic aperture-based on-chip microscopy , 2015, Light: Science & Applications.

[14]  Derek Tseng,et al.  Targeted DNA sequencing and in situ mutation analysis using mobile phone microscopy , 2017, Nature Communications.

[15]  Aydogan Ozcan,et al.  Smart-phone based computational microscopy using multi-frame contact imaging on a fiber-optic array. , 2013, Lab on a chip.

[16]  Yibo Zhang,et al.  Wide-field computational imaging of pathology slides using lens-free on-chip microscopy , 2014, Science Translational Medicine.

[17]  Derek Tseng,et al.  Fluorescent imaging of single nanoparticles and viruses on a smart phone. , 2013, ACS nano.

[18]  Philippe Colantoni,et al.  High‐end colorimetric display characterization using an adaptive training set , 2011 .

[19]  Yibo Zhang,et al.  Sparsity-based multi-height phase recovery in holographic microscopy , 2016, Scientific Reports.

[20]  A. Ozcan,et al.  Maskless imaging of dense samples using pixel super-resolution based multi-height lensfree on-chip microscopy , 2012, Optics Express.

[21]  Steve Feng,et al.  Rapid imaging, detection and quantification of Giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning. , 2015, Lab on a chip.

[22]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[23]  Alain Trémeau,et al.  Color calibration of an RGB camera mounted in front of a microscope with strong color distortion. , 2013, Applied optics.

[24]  Shuxue Quan,et al.  Digital camera filter design for colorimetric and spectral accuracy , 2001 .

[25]  Aydogan Ozcan,et al.  Mobile phones democratize and cultivate next-generation imaging, diagnostics and measurement tools. , 2014, Lab on a chip.

[26]  Dani Lischinski,et al.  Colorization using optimization , 2004, ACM Trans. Graph..

[27]  A. Ozcan,et al.  Pixel super-resolution using wavelength scanning , 2015, Light: Science & Applications.

[28]  Aydogan Ozcan,et al.  Field-portable wide-field microscopy of dense samples using multi-height pixel super-resolution based lensfree imaging. , 2012, Lab on a chip.

[29]  S. Mallat A wavelet tour of signal processing , 1998 .

[30]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .