COMPUTATIONAL IMAGING, SENSING AND DIAGNOSTICS
Aydogan Ozcan1,2,3,4,*
Electrical Engineering Department, University of California, Los Angeles, CA, 90095, USA
2
Bioengineering Department, University of California, Los Angeles, CA, 90095, USA
3
California NanoSystems Institute, University of California, Los Angeles, CA, 90095, USA
4
Department of Surgery, David Geffen School of Medicine, University of California, Los Angeles, CA,
90095, USA
http://innovate.ee.ucla.edu/ & http://biogames.ee.ucla.edu/ & http://org.ee.ucla.edu/
1
ABSTRACT
In this plenary contribution, we review our recent progress on the use of computational biophotonics techniques for
microscopy, tomography, sensing and diagnostics applications, with a specific emphasis on telemedicine and global
health. The use of computational imaging and sensing techniques simplifies the design and the architecture of various
microscopy and diagnostics tools while also providing new opportunities to collect and harness the power of large scale
biomedical data due to the global connectivity of these emerging computational micro-analysis devices integrated on e.g.,
cellphones.
KEYWORDS: Computational imaging, sensing, diagnostics, point-of-care, on-chip microscopy, lensfree imaging,
holographic imaging, lensfree tomography, telemedicine, cellphone based microscopy, cellphone based diagnostics
INTRODUCTION
Our research lab at UCLA focuses on the use of computational photonics to create new optical microscopy, sensing
and diagnostics technologies that significantly improve our toolset for probing micro- and nano-scale objects while also
simplifying the designs of these analysis tools, making them highly suitable for point-of-care and home use, as well as for
(a)
(c)
(b)
(f)
(g)
(d)
(h)
(i)
(e)
(j)
Figure 1: Computational Micro-analysis, Sensing and Diagnostic Tools Running on Cellphones (a) A lensfree holographic microscope that weighs ~ 45 grams is shown.[1],[6] (b) A cellphone device that is modified based on the same
lensless holographic microscopy principle is shown.[7] This cost-effective attachment to the cellphone enables lightweight and compact microscopy for imaging various bodily fluids including whole blood, urine, sputum etc., and can
be used for diagnosis of infectious diseases as well as screening of pathogens in water sources. (c) A wide-field fluorescent microscope that is installed on a cell-phone using a compact and cost-effective optical interface is illustrated.[9-12] (d) An imaging fluorescent flow-cytometer installed on a cellphone. An inexpensive micro-fluidic chip is used
to pump liquid specimen into the imaging volume of the cellphone camera, such that movies of fluorescent
cells/particles are captured for further analysis of their concentration in the liquid.[10] (e-f) Cell-phone attachment for
automated reading, quantification and digital storage of immunochromatographic Rapid Diagnostic Tests (RDTs).[16]
The RDT that is inserted onto the cell-phone is digitally imaged using the interface installed on the cell-phone, where
diagnosis is automatically determined and transmitted (along with the raw image) to a central server using a smart
application running on the phone. The same attachment can work with different available RDTs (including malaria,
HIV and TB RDTs) and accurately analyze each test strip and the associated detection/control lines. (g-h) A compact
and cost-effective imaging cytometry platform installed on a cell-phone for the measurement of the density of red and
white blood cells as well as hemoglobin concentration in blood samples.[12] (i) Picture of the optical attachment for
E. coli detection on a cell-phone using quantum dot based sandwich assay in glass capillary tubes.[11] The entire attachment to the cell-phone weighs ~28 grams (~1 ounce) and has dimensions of ~3.5 x 5.5 x 2.4 cm. This compact and
light-weight unit has an imaging field-of-view of 11 mm x 11 mm and can monitor ~10 capillary tubes all in parallel,
with a detection sensitivity of ~5-10 CFU/mL. (j) A personalized allergen testing platform running on a cellphone that
images and automatically analyses colorimetric assays toward sensitive and specific detection of allergens in food
samples.[13] A sensitivity level of ~1 ppm for peanut detection has been demonstrated using this cellphone based design. More information on these projects of our group can be reached at our group website.
978-0-9798064-6-9/µTAS 2013/$20©13CBMS-0001
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17th International Conference on Miniaturized
Systems for Chemistry and Life Sciences
27-31 October 2013, Freiburg, Germany
resource poor settings.[1-16] Through
these emerging technologies, we create
integrated self-learning systems and
networks, specifically for biomedical
micro-analysis and diagnosis, aiming to
impact various global health challenges
with highly sensitive, specific and yet
remarkably cost-effective and compact
solutions (see for example Figures 1-2).
RESULTS
In this plenary talk I will introduce
various
imaging
and
detection
architectures that can compensate in the
digital domain for the lack of complexity
of optical components by use of novel
theories and numerical algorithms to
address the immediate needs and
requirements of telemedicine and global
health. Specifically, I will present an onchip cytometry and microscopy platform
that utilizes cost-effective and compact
components to enable digital recognition
and 3D microscopic/tomographic imaging
of cells with sub-cellular resolution over a
large field of view (FOV) without the need
for any lenses, bulky optical components
or coherent sources such as lasers.[1-2]
This incoherent holographic imaging and
diagnostic modality has orders of
magnitude improved light collection Figure 2: Digital BioGames for Crowd-sourced Tele-pathology and Teleefficiency and is robust to misalignments diagnosis. (Top) Our BioGame can be played on multiple platforms, inwhich eliminates potential imaging cluding cellphones, tablet PCs and web browsers. The gamers can diagartifacts or the need for realignment, nose the infection status of individual cells by killing them or putting them
making it highly suitable for field use. in a blood bank. The decisions of multiple diagnosers are then combined to
Applications of this lensfree on-chip create accurate diagnoses at the single cell level.[14-15] Apart from telemicroscopy platform to high-throughput pathology applications, this BioGames platform could also be rather imimaging and automated counting of whole portant for wide-scale training and education of health-care professionals
blood cells, monitoring of HIV+ patients or medical students. (Bottom) Since we publicly launched this BioGames
(through CD4 and CD8 T cell counting) platform, we have received >1.9 million diagnostics results at the single
and detection of waterborne parasites cell level from >2,200 participants across >75 different countries.
towards rapid screening of water quality For more information: http://biogames.ee.ucla.edu/
will also be demonstrated. Further, I will
discuss lensfree implementations of various other computational imaging modalities on the same platform such as pixel
super-resolution imaging, lensfree on-chip tomography, holographic opto-fluidic microscopy and tomography. I will also
demonstrate lensfree on-chip imaging of fluorescently labeled cells over an ultra wide field of view of >8 cm 2, which
could be especially important for rare cell analysis (e.g., detection of circulating tumor cells), as well as for highthroughput screening of DNA/protein micro-arrays.
Finally, I will introduce digital BioGames concept that we have recently created for crowd-sourced tele-pathology and
tele-diagnosis (see Figure 2). In this research theme of our group, we have shown that by utilizing the innate visual
recognition and learning capabilities of human crowds it is possible to conduct reliable microscopic analysis of
biomedical samples and make diagnostics decisions based on crowd-sourcing of microscopic data through intelligently
designed and entertaining games (which we term as BioGames) that are interfaced with artificial learning and processing
back-ends. In our recent results,[14-15] we have demonstrated that for binary diagnostics decisions (e.g., infected vs.
uninfected cells, as in the case of malaria diagnosis with blood smears), using crowd-sourced games it is possible to
approach the accuracy of medical experts in making such diagnoses. As further illustrated in Figure 2, this BioGames
platform relies on the participation of non-expert as well as expert crowds of individuals by playing serious games that
are designed around specific pathology tasks.
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ACKNOWLEDGEMENTS
Ozcan Research Group at UCLA gratefully acknowledges the support of Nokia University Cooperation Funding, the
Presidential Early Career Award for Scientists and Engineers (PECASE), Army Research Office (ARO) Life Sciences
Division, ARO Young Investigator Award, National Science Foundation (NSF) CAREER Award, NSF CBET Division
Biophotonics Program, NSF Emerging Frontiers in Research and Innovation (EFRI) Award, Office of Naval Research
(ONR) Young Investigator Award and National Institutes of Health (NIH) Director's New Innovator Award
DP2OD006427 from the Office of the Director, National Institutes of Health.
REFERENCES
[1]
A. Greenbaum, W. Luo, T-W. Su, Z. Göröcs, L. Xue, S.O. Isikman, A.F. Coskun, O. Mudanyali, and A. Ozcan,
“Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy,” Nature Methods
DOI:10.1038/nmeth.2114 (2012)
[2]
O. Mudanyali, E. McLeod, W. Luo, A. Greenbaum, A.F. Coskun, Y. Hennequin, C. Allier and A. Ozcan,
“Wide-field optical detection of nano-particles using on-chip microscopy and self-assembled nano-lenses,” Nature Photonics DOI: 10.1038/NPHOTON.2012.337 (2013)
[3]
T-W. Su, L. Xue and A. Ozcan, “High-throughput lensfree 3D tracking of human sperms reveals rare statistics of
helical trajectories,” Proceedings of the National Academy of Sciences (PNAS) DOI: 10.1073/pnas.1212506109 (2012)
[4]
S.O. Isikman, W. Bishara, S. Mavandadi, F.W. Yu, S. Feng, R. Lau and A. Ozcan, “Lensfree Optical Tomographic Microscope with a Large Imaging Volume on a Chip,” Proceedings of the National Academy of Sciences (PNAS)
DOI: 10.1073/pnas.1015638108 (2011)
[5]
S.O. Isikman, W. Bishara, U. Sikora, O. Yaglidere, J. Yeah, and A. Ozcan, “Field-Portable Lensfree Tomographic Microscope,” Lab on a Chip DOI:10.1039/C1LC20127A (2011)
[6]
O. Mudanyali, D. Tseng, C. Oh, S.O. Isikman, I. Sencan, W. Bishara, C. Oztoprak, S. Seo, B. Khademhosseini,
and A. Ozcan, “Compact, Light-weight and Cost-effective Microscope based on Lensless Incoherent Holography for Telemedicine Applications” Lab on a Chip, DOI:10.1039/C000453G (2010)
[7]
D. Tseng, O. Mudanyali, C. Oztoprak, S.O. Isikman, I. Sencan, O. Yaglidere and A. Ozcan, “Lensfree Microscopy on a Cell-phone” Lab on a Chip DOI:10.1039/c003477k (2010)
[8]
W. Bishara, U. Sikora, O. Mudanyali, T. Su, O. Yaglidere, S. Luckhart, and A. Ozcan, “Holographic pixel super-resolution in portable lensless on-chip microscopy using a fiber-optic array,” Lab on a Chip
DOI:10.1039/C0LC00684J (2011)
[9]
H. Zhu, O. Yaglidere, T. Su, D. Tseng, and A. Ozcan, “Cost-effective and Compact Wide-field Fluorescent Imaging on a Cell-phone”, Lab on a Chip, DOI:10.1039/C0LC00358A (2010)
[10]
H. Zhu, S. Mavandadi, A.F. Coskun, O. Yaglidere, and A. Ozcan, “Optofluidic fluorescent imaging cytometry
on a cell-phone,” Analytical Chemistry DOI: 10.1021/ac201587a (2011)
[11]
H. Zhu, U. Sikora, and A. Ozcan, “Quantum dot enabled detection of Escherichia coli using a cell-phone,” Analyst DOI: 10.1039/C2AN35071H (2012)
[12]
H. Zhu, I. Sencan, J. Wong, S. Dimitrov, D. Tseng, K. Nagashimaa, and A. Ozcan, “Cost-effective and Rapid
Blood Analysis on a Cell-phone,” Lab on a Chip DOI:10.1039/C3LC41408F (2013)
[13]
A.F. Coskun, J. Wong, D. Khodadadi, R. Nagi, A. Tey, and A. Ozcan, “A personalized food allergen testing
platform on a cellphone,” Lab on a Chip DOI:10.1039/C2LC41152K (2012)
[14]
S. Mavandadi, S. Dimitrov, S. Feng, F. Yu, U. Sikora, O. Yaglidere, S. Padmanabhan, K. Nielsen, and A. Ozcan,
“Distributed Medical Image Analysis and Diagnosis through Crowd-Sourced Games: A Malaria Case Study,” PLoS ONE
DOI:10.1371/journal.pone.0037245 (2012)
[15]
S. Mavandadi, S. Feng, F. Yu, S. Dimitrov, K. Nielsen, W.R. Prescott, and A. Ozcan, “A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using TeleMicroscopy,” PLoS ONE DOI:10.1371/journal.pone.0046192 (2012)
[16]
O. Mudanyali, S. Dimitrov, U. Sikora, S. Padmanabhan, I. Navruz, and A. Ozcan, “Integrated Rapid-DiagnosticTest Reader Platform on a Cellphone,” Lab on a Chip DOI:10.1039/C2LC40235A (2012)
CONTACT
*Aydogan Ozcan; [email protected]
http://innovate.ee.ucla.edu/ & http://biogames.ee.ucla.edu/ & http://org.ee.ucla.edu/
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