The advancement of angular domain imaging in mesoscopic reflectance multispectral imaging is reported. The key component is an angular filter array that performs the angular filtration of the back-scattered photons and generates image contrast due to the variances in tissue optical properties. The proposed modality enables multispectral imaging of subsurface features for samples too thick for transillumination angular domain spectroscopic imaging (ADSI) approaches. The validation was carried out with tissue-mimicking phantoms with multiple absorptive features embedded below the surface. Multispectral images in the range of 666 to 888 nm clearly revealed the location of the features with the background scattering levels up to 20 cm−1. The shape of the features was recoverable at depths of up to three to four times the transport mean free path. The spatial resolution was <1 mm and the field-of-view was larger than 2.5 cm×3.0 cm. Furthermore, the attenuation spectra of measured absorptive features were successfully extracted. Target detectability and imaging quality with different background scattering levels, target depths, and illumination focal depths were discussed, as well as the capability of ADSI in reflectance optical mesoscopic imaging and its potential applications.
The Radial Angular Filter Array (RAFA) is a novel optical filter consisting of a radially-distributed series of micromachined
channels with a focal length of a few millimeters. The RAFA filters photons passing through the focal point
according to the propagation direction and has proven to be capable of collecting the angular distribution and the spectral
information of photons simultaneously and non-invasively, which allows angle-resolved spectroscopic measurement of a
turbid medium. To explore the feasibility of using this device to characterize the optical abnormalities in human tissues,
we tested the performance of an angle-resolved RAFA-based spectroscopy system to detect absorption targets embedded
within a tissue-mimicking phantom. The body of the phantom was made of 0.1% IntralipidTM/agarose gel (7 mm in
thickness) and the targets were spherical (1.5 mm in radius) and contained 10 μM Indocyanine Green (ICG). The
illumination source was a broadband near infrared (NIR) collimated beam. Photons were angularly filtered by the RAFA
and spectrally resolved by a pushbroom spectrometer. The experimental results confirmed that the RAFA preferentially
filtered photons that carried absorption and scattering information of the embedded targets.
The Radial Angular Filter Array (RAFA) is a novel optical filter consisting of a radially-distributed series of micromachined
channels, which converge upon a focal point several millimeters away from the edge of the device. It is
designed to measure the angular distribution of light emitted from an object located at the focal point and is capable of
selecting ballistic and quasi-ballistic photons at specific angles out of strong background noise due to scattering. We
hypothesized that the device might be useful for examining optically absorbing features below the surface of a turbid
medium via a depth mapping approach. In order to validate this concept, experiments were performed with a focused
laser beam, a series of IntralipidTM solutions (0.1 wt% to 1.0 wt%), a 0.5 mm diameter graphite rod (absorber), and a
RAFA optically coupled to a line camera. By scanning the position of the rod and comparing the light scattering profiles
obtained by the RAFA at each scanning step, the location and the depth of the rod were successfully identified. Future
work will be directed toward studying the performance of the technique with a collimated broadband illumination beam
for spectroscopic applications.
The angular filter array (AFA) is a silicon micro-machined optical collimator, which only accepts photons propagating
within a narrow solid angle. It can be used to select photons exiting an imaging sample along a specific direction. This
paper describes a novel Angular Domain Spectroscopic Imaging (ADSI) technique that utilizes deep illumination from
the front surface of the sample and a camera with an AFA to image features embedded inside a turbid medium. This
approach permitted spectroscopic imaging of turbid samples too thick to be imaged in a trans-illumination setup. The
tissue-mimicking test phantom contained three groups of Indocyanine Green doped inclusions at depths from 1 to 3 mm
embedded within an IntralipidTM/agarose gel. The sample was scanned across the AFA and the intensity of the back
scattered light along the direction normal to the surface was acquired as a function of location and wavelength. The
resultant spectral images were captured and analyzed. The experiments demonstrated that ADSI could detect subsurface
features that differed in wavelength-dependent absorption and/or scattering properties from the surrounding medium
with the deep illumination configuration. Deep illumination ADSI may be useful as a non-invasive tissue imaging tool.
The Radial Angular Filter Array (RAFA) is a novel silicon micro-machined optical filter for real-time high resolution
measurement of the angular distribution of scattered photons. It includes a radially-distributed series of micro-channels
facing a focal point that is several millimeters away from the edge of the device. In this work, three RAFA designs were
devised to enhance the angular resolution, while lessening the complexity of the output coupling. These new RAFA
designs solved issues associated with a previous prototype device, including the signal loss in high angle channels and
light leakage beyond the acceptance angle. Typically, channels in the RAFA are 60 μm deep with a minimum length of
10 mm. To characterize the RAFA designs, we used an incoherent broadband source, collimation optics, turbid samples,
and a spectrometer. The tests identified which design features resulted in improved performance, including the preferred
output coupling structure, the recommended near specular direction blocking range, the choice of constant aspect ratio or
solid angle, and other geometrical parameters.
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