The Brillouin scattering spectra of biological systems have shown to be inherently related to the intrinsic elasticity and molecular constants of tissues involved. Our approach of combining confocal microscopy and high-resolution Brillouin spectroscopy via a virtual imaging phase array enabled 10-microsecond single-pixel acquisition time without dedicated spatial filtering. Such an approach is adapted via a single-frequency fiber-coupled 780-nm wavelength laser, frequency stabilized by Rb-D2 absorption line, polarization extinction scheme, ASE filtering, heated Rb-vapor Rayleigh-scattering absorbent, and spectroscopic EMCCD camera, unified as CMS-VIPA: confocal virtual-imaging phase array microscopespectrometer. Steady strengthening of corneal bulk modulus was observed via spectral shifts of Brillouin scattering from 5.0-5.2 GHz in untreated porcine eyes to 5.7-5.9 GHz in ones cross-linked in riboflavin plus UV-A light at 0.7-0.9 GHz level of enhancement. The cross-linking depths reaching 300400 microns were measured, as predicted by modeling. A noncontact Brillouin spectroscopic microscopy system for in-vivo corneal elasticity measurement is under development.
Segmentation of the retinal nerve fiber layer (RNFL) from swept source polarization-sensitive optical coherence
tomography (SS-PSOCT) images is required to determine RNFL thickness and calculate birefringence. Traditional
RNFL segmentation methods based on image processing and boundary detection algorithms utilize only optical
reflectivity contrast information, which is strongly affected by speckle noise. We present a novel approach to segment
the retinal nerve fiber layer (RNFL) using SS-PSOCT images including both optical reflectivity and phase retardation
information. The RNFL anterior boundary is detected based on optical reflectivity change due to refractive index
difference between the vitreous and inner limiting membrane. The posterior boundary of the RNFL is a transition zone
composed of birefringent axons extending from retinal ganglion cells and may be detected by a change in birefringence.
A posterior boundary detection method is presented that segments the RNFL by minimizing the uncertainty of RNFL
birefringence determined by a Levenberg-Marquardt nonlinear fitting algorithm. Clinical results from a healthy
volunteer show that the proposed segmentation method estimates RNFL birefringence and phase retardation with lower
uncertainty and higher continuity than traditional intensity-based approaches.
Pulsed light emitted from a near infrared (λ=800nm) femtosecond laser is capable of plasma induced photodisruption of
various materials. We used femtosecond laser pulses to ablate human urinary calculi. Femtosecond pulsed laser
interaction with urinary calculi was investigated with various stone compositions, different incident fluences and number
of applied pulses. Spectral-domain optical coherence tomography was used to image cross sections of ablation craters on
the surface of urinary calculi. Our results indicate that femtosecond laser pulses can ablate various calculi compositions.
Crater diameter and depth varies from tens of microns to several hundred microns when up to 1000 pulses were applied.
Future studies are required to determine if pulsed near infrared femtosecond laser pulses can be applied clinically for
lithotripsy of urinary calculi.
Retinal nerve fiber layer (RNFL) thickness, a measure of glaucoma progression, can be measured in images acquired
by spectral domain optical coherence tomography (OCT). The accuracy of RNFL thickness estimation, however, is
affected by the quality of the OCT images. In this paper, a new parameter, signal deviation (SD), which is based on the
standard deviation of the intensities in OCT images, is introduced for objective assessment of OCT image quality. Two
other objective assessment parameters, signal to noise ratio (SNR) and signal strength (SS), are also calculated for each
OCT image. The results of the objective assessment are compared with subjective assessment. In the subjective
assessment, one OCT expert graded the image quality according to a three-level scale (good, fair, and poor). The OCT
B-scan images of the retina from six subjects are evaluated by both objective and subjective assessment. From the
comparison, we demonstrate that the objective assessment successfully differentiates between the acceptable quality
images (good and fair images) and poor quality OCT images as graded by OCT experts. We evaluate the performance
of the objective assessment under different quality assessment parameters and demonstrate that SD is the best at
distinguishing between fair and good quality images. The accuracy of RNFL thickness estimation is improved
significantly after poor quality OCT images are rejected by automated objective assessment using the SD, SNR, and
SS.
KEYWORDS: Tissues, Melanoma, Monte Carlo methods, Laser tissue interaction, 3D modeling, Temperature metrology, Radiometry, Tissue optics, Pulsed laser operation, Absorption
Melanoma is a malignant tumor of melanocytes which are found predominantly in skin. Melanoma is one of the rarer
types of skin cancer but causes the majority of skin cancer related deaths. The staging of malignant melanoma using
Breslow thickness is important because of the relationship to survival rate after five years. Pulsed photothermal
radiometry (PPTR) is based on the time-resolved acquisition of infrared (IR) emission from a sample after pulsed laser
exposure. PPTR can be used to investigate the relationship between melanoma thickness and detected radiometric
temperature using two-layer tissue phantoms. We used a Monte Carlo simulation to mimic light transport in melanoma
and employed a three-dimensional heat transfer model to obtain simulated radiometric temperature increase and, in
comparison, we also conducted PPTR experiments to confirm our simulation results. Simulation and experimental
results show similar trends: thicker absorbing layers corresponding to deeper lesions produce slower radiometric
temperature decays. A quantitative relationship exists between PPTR radiometric temperature decay time and thickness
of the absorbing layer in tissue phantoms.
We introduce a method based on optical reflectivity changes to segment the retinal nerve fiber layer (RNFL) in images recorded using swept source spectral domain optical coherence tomography (OCT). The segmented image is used to determine the RNFL thickness. Simple filtering followed by edge detecting techniques can successfully be applied to segment the RNFL from recorded images and estimate RNFL thickness. The method is computationally more efficient than previously reported approaches. Higher computational efficiency allows faster segmentation and provides the ophthalmologist segmented retinal images that better utilize advantages of spectral domain OCT instrumentation. OCT B-scan and fundus images of the retina are recorded for 5 patients. The segmentation method is applied on B-scan images recorded from all patients. An expert ophthalmologist separately demarcates the RNFL layer in the OCT images from the same patients in each B-scan image. Results from automated image processing software are compared to the boundary demarcated by the expert ophthalmologist. The absolute error between the boundaries demarcated by the expert and the algorithm is expressed in terms of area and is used as an error metric. Ability of the algorithm to accurately segment the RNFL in comparison with an expert ophthalmologist is reported.
We present the development and demonstration of a novel technique for microscopic analysis of urine particles. Casts
and crystals in urine are indicative of clinically important abnormalities. Current urinalysis techniques using flow
cytometry and image analysis are limited by their inability to detect, identify and classify crystals and casts. Casts,
crystals and yeast cells reported by current automated urine particle analyzers must be confirmed by a second
microscopic review involving a human operator to prevent false positives. Human examination of suspect urine samples
is resource intensive and time consuming. We introduce a new imaging method to add functionality for recognition of
casts and crystals in urine. Our approach uses a polarization microscopy technique to aid classification of crystals, casts
and other urine particles. Crystals and casts in urine exhibit unique interference patterns when imaged using a fixed
polarizer and analyzer in a crossed configuration. These interference patterns are a measure of birefringence (retardation
angle) of the cast or crystal being imaged. Preliminary experiments indicate that uric acid shows a polarization color, and
larger crystals exhibit a series of concentric black lines. We show that these unique 'signatures' when used in
conjunction with a hierarchical pattern recognition technique can reliably classify the analytes with improved accuracy.
The new imaging technique combined with the classification algorithm can address the shortcomings of current
urinalysis techniques; and provide quicker and more accurate results.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.