Compiled by Photonics Spectra staff
LOS ANGELES – A new lens-free chip and image processing algorithm combines optical
sensors, holography and digital tomography to render high-resolution, high-contrast
images while avoiding the limitations of lens-based optical microscopy.
Developed by scientists at the University of California, the “sensor”
is a 5-megapixel CMOS chip with 2.2-μm pixels. It is similar to the sensors
found in a Blackberry or iPhone, except that it is monochrome rather than RGB, said
Aydogan Ozcan, associate professor of electrical engineering at UCLA’s Henry
Samueli School of Engineering and Applied Science.
The team faced the challenge of reducing noise artifacts resulting
from spatial and temporal coherence due to illuminating the sample with a laser
– especially at oblique angles. To overcome this, the investigators replaced
laser illumination with partially coherent light that emanated from an aperture
of ~0.05 to 0.1 mm in diameter, with a bandwidth of 1 to 10 nm. They found that
recording in-line holograms using partial coherence provided a gating function that
allowed the device to filter noise that is beyond a defined resolution level.
They developed a sample illumination approach that rotates the
partially coherent light source around the sample, rather than requiring the platform
to be rotated within the illumination field. The lens-free optical tomographic microscope
features many new innovations, but three are key, according to Ozcan: partially
coherent illumination with unit-magnification, pixel superresolution to achieve
deeply subpixel lateral resolution and dual-axis tomographic illumination.
Primary applications for the lens-free microscopy technique could
include cell and developmental biology – especially in microfluidic integration.
“Microfluidic integration would permit rather interesting
lab-on-a-chip devices that could do optofluidic microscopy and tomography (also
known as holographic optofluidic microscopy, or HOM) on the same chip,” Ozcan
The technology also could enable in vivo applications, if further
miniaturization and integration were to take place. The group’s work appeared
April 19, 2011, in Proceedings of the National Academy of Sciences (doi: 10.1073/pnas.