Multi-color LUCAS: Lensfree On-chip Cytometry Using Tunable Monochromatic Illumination and Digital Noise Reduction

  • Sungkyu Seo
  • Ting-Wei Su
  • Anthony Erlinger
  • Aydogan OzcanEmail author


It has been recently demonstrated that rapid on-chip monitoring of a homogenous cell solution within an ultra-large field-of-field of ~10 cm2 is feasible by recording the classical diffraction pattern of each cell in parallel onto an opto-electronic sensor array under incoherent white light illumination. Here we present several major improvements over this previous approach. First, through experimental results, we illustrate that the use of narrowband short wavelength illumination (e.g., at ~300 nm) significantly improves the digital signal-to-noise ratio of the cell diffraction signatures, which translates itself to a significant increase in the depth-of-field (e.g., ~5 mm) and hence the sample volume (e.g., 5 mL) that can be imaged. Second, we also illustrate that by varying the illumination wavelength, the texture of the recorded cell signatures can be tuned to enable automated identification and characterization of a target cell type within a heterogeneous cell solution. Third, a hybrid imaging scheme that combines two different wavelengths is also demonstrated to improve the uniformity and signal-to-noise ratio of the recorded cell diffraction images. Finally, we demonstrate that a further improvement in image quality can be achieved by utilizing adaptive digital filtering. These noteworthy improvements are especially quite important to achieve more reliable performance for rapid detection and counting of a target cell type among many other cells present within a heterogeneous sample volume of e.g., ~5 mL. This incoherent on-chip imaging platform may have a significant impact especially for medical diagnostic applications related to global health problems such as HIV monitoring.


High-throughput cell counting On-chip imaging Lensfree imaging Lensless imaging LUCAS Incoherent imaging Medical diagnostics Point-of-care applications Global health problems HIV monitoring Digital noise reduction Adaptive filtering 

Supplementary material

12195_2008_18_MOESM1_ESM.doc (240 kb)
Figure S1 LUCAS images for multiple layers of a heterogeneous solution. Each mixture layer contains 5 μm diameter micro-beads, red blood cells, and yeast cells (S. Pombe, alive), all suspended in 1× PBS solution. (a) The total volume, that was imaged using LUCAS within less than 1 s was ~2.3 mL. (b) Shows part of the LUCAS image corresponding to the multi-layer structure of (a), and (c–d) are zoomed-in images of (b), taken within white dotted and dashed frames, where each shadow signature is circled with different colors uniquely identifying the type and height of micro-objects (DOC 240 kb)
12195_2008_18_MOESM2_ESM.doc (711 kb)
Figure S2 Conventional transmission microscope images of micro-beads (D = 3 μm), red blood cells, alive yeast cells, and fixed yeast cells acquired through a 10× objective lens are shown in (a, d, g, j). Corresponding LUCAS images of the same region of interest illuminated with 300 nm wavelength (b, e, h, k) and white light illumination (c, f, i, l) clearly illustrate that a shorter illumination wavelength provides a significant SNR enhancement of e.g., >10 dB (DOC 711 kb)
12195_2008_18_MOESM3_ESM.doc (156 kb)
Figure S3 (a) At a short DOF of S/n = 272 μm, a shorter illumination wavelength (300 nm) shows a strong LUCAS signal, but it also exhibits quite poor texture information. By increasing the illumination wavelength, this uniformity issue can be partially solved, but SNR also drops rapidly with the increasing wavelength (b–c). (d) By combining 300 and 950 nm LUCAS images using the Hybrid Approach, the texture uniformity of fixed yeast cells could be maintained while still achieving an improved SNR performance similar to short wavelength illumination (DOC 157 kb)
12195_2008_18_MOESM4_ESM.doc (368 kb)
Figure S4 LUCAS image improvement using digital noise reduction filters for fixed yeast cells is illustrated. A series of digital filters were applied to the background subtracted LUCAS image shown in (a). These noise reduction filters, i.e., enhanced Lee filter (j), Lee filter (d), Kuan filter (e), Yu filter (g), ‘A Trous’ wavelet transform based filter (i), hybrid median filter (c), symmetric nearest-neighbor filter (b), averaged filter (f), and adaptive Wiener filter (h), showed significant improvements in SNR; for instance the enhanced Lee filter enhanced the digital SNR by more than 7 dB (DOC 368 kb)
12195_2008_18_MOESM5_ESM.doc (292 kb)
Figure S5 LUCAS image improvement using digital noise reduction filters for red blood cells is illustrated. Similar results as in Fig. S4 are obtained for the LUCAS signatures of red blood cells (DOC 292 kb)


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Copyright information

© Biomedical Engineering Society 2008

Authors and Affiliations

  • Sungkyu Seo
    • 1
  • Ting-Wei Su
    • 1
  • Anthony Erlinger
    • 1
  • Aydogan Ozcan
    • 1
    • 2
    • 3
    Email author
  1. 1.Electrical Engineering DepartmentUniversity of CaliforniaLos AngelesUSA
  2. 2.Biomedical Engineering IDPUniversity of CaliforniaLos AngelesUSA
  3. 3.California Nano Systems Institute (CNSI)University of CaliforniaLos AngelesUSA

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