Previously, we have reported on advances made with our CTIA based TEC-less SWIR cameras [1, 2, 3, 4]. Here, we
present our next generation TEC-less small SWaP SWIR cameras which are built upon a current mirror type pixel. The
standard packaged FPAs are modified by replacing the TECs with copper shims. These FPAs are incorporated into
cameras with similar electronics to our COTS cameras (CSX and JSX series), and then fully characterized from -30 °C
to 60 °C. From these data, we developed algorithms that provide temperature-based corrections resulting in nonuniformity
of approximately 0.5 % over the entire operating temperature. Additionally, over this range, the 640 x 512
resolution camera exhibited power consumption in the 1.2-1.3 W range, whereas the 1280 x 1024 camera exhibited
power consumption in the 1.3-1.4 W range.
Size, weight, and power (i.e.: Small SWaP) are increasingly recognized as the primary drivers in the enablement of high-volume man-portable SWIR imaging systems. Several low power advancements are described for a 1.3 Mpixel SWIR imaging platform capable of operating at a power budget of approximately 1.7 microwatts/pixel. Techniques such as reducing overall system memory bandwidth, low-voltage operation, and parameterized non-uniform corrections (PNUC) are described. Even at such reduced power consumption, full imaging performance at 30 frames per second is realized across an extended operating range of -40°C to 70°C.
Significant research and development efforts are currently underway to produce robust Short Wave Infrared (SWIR)
camera systems with low power consumption. Substantial improvements in power can be achieved through the
elimination of the thermoelectric cooler (TEC) on the FPA. Removing the TEC from the system introduces temperature
as a significant parameter effecting FPA spatial uniformity, effectively requiring more complex temperature dependent
non-uniformity image correction algorithms. We present here our latest work in developing a parameterized
non-uniformity correction algorithm for a low-power no-TEC camera. The camera used in these experiments is the
Goodrich GA1280J-15 high resolution, high sensitivity, InGaAs SWIR camera operating at 30 Hz, and modified to
operate without a TEC. The FPA size is 1280 x 1024 pixels, with a 15 μm pitch. Typical power when operating with
parameterized non-uniformity corrections consumption is 3 W or less. The camera under test was mounted inside of an
environmental chamber and images at varying illumination levels were acquired from -50 to 70 °C with a 10 °C step.
Analysis of these images yielded the optimal orders and coefficients for a parameterized non-uniformity corrections
model consisting of a sum of polynomials in raw counts, and FPA temperature. The optimized model was determined to
be 1st order in counts and 5th order in FPA temperature, with an average R2 between the target counts and corrected
counts of 0.999 ± 0.001, and average reduction of spatial noise of 83 ± 7 % across all camera operational modes.
We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided.
Jelena Mirkovic, Condon Lau, Sasha McGee, Chung-Chieh Yu, Jonathan Nazemi, Luis Galindo, Victoria Feng, Teresa Darragh, Antonio de las Morenas, Christopher Crum, Elizabeth Stier, Michael Feld, Kamran Badizadegan
It has long been speculated that underlying variations in tissue anatomy affect in vivo spectroscopic measurements. We investigate the effects of cervical anatomy on reflectance and fluorescence spectroscopy to guide the development of a diagnostic algorithm for identifying high-grade squamous intraepithelial lesions (HSILs) free of the confounding effects of anatomy. We use spectroscopy in both contact probe and imaging modes to study patients undergoing either colposcopy or treatment for HSIL. Physical models of light propagation in tissue are used to extract parameters related to tissue morphology and biochemistry. Our results show that the transformation zone, the area in which the vast majority of HSILs are found, is spectroscopically distinct from the adjacent squamous mucosa, and that these anatomical differences can directly influence spectroscopic diagnostic parameters. Specifically, we demonstrate that performance of diagnostic algorithms for identifying HSILs is artificially enhanced when clinically normal squamous sites are included in the statistical analysis of the spectroscopic data. We conclude that underlying differences in tissue anatomy can have a confounding effect on diagnostic spectroscopic parameters and that the common practice of including clinically normal squamous sites in cervical spectroscopy results in artificially improved performance in distinguishing HSILs from clinically suspicious non-HSILs.
Raman spectroscopy is a rapid nondestructive technique capable of assaying chemicals in human artery tissues and characterizing atherosclerotic plaques in vivo, but clinical applications through optical fiber-based catheters have been hindered by large background signals generated within the fibers. Previous workers realized that this background was reduced significantly in the high wavenumber (HWVN) Raman region (~2400 cm−1 to ~3800 cm−1), and with proper selection of optical fibers, one could collect quality Raman spectra remotely via a single optical fiber with no additional filters or optics. This study compared lipid concentrations in coronary artery tissue that were determined with chemical assay techniques to those estimated from HWVN Raman spectra collected through a single optical fiber. The standard error of predictions between the Raman and chemical assay techniques were small for cholesterol and esterified cholesterols, at 1.2% and 2.7%, respectively.
Using diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy, we have developed an algorithm that successfully classifies normal breast tissue, fibrocystic change, fibroadenoma, and infiltrating ductal carcinoma in terms of physically meaningful parameters. We acquire 202 spectra from 104 sites in freshly excised breast biopsies from 17 patients within 30 min of surgical excision. The broadband diffuse reflectance and fluorescence spectra are collected via a portable clinical spectrometer and specially designed optical fiber probe. The diffuse reflectance spectra are fit using modified diffusion theory to extract absorption and scattering tissue parameters. Intrinsic fluorescence spectra are extracted from the combined fluorescence and diffuse reflectance spectra and analyzed using multivariate curve resolution. Spectroscopy results are compared to pathology diagnoses, and diagnostic algorithms are developed based on parameters obtained via logistic regression with cross-validation. The sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy (total efficiency) of the algorithm are 100, 96, 69, 100, and 91%, respectively. All invasive breast cancer specimens are correctly diagnosed. The combination of diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy yields promising results for discrimination of breast cancer from benign breast lesions and warrants a prospective clinical study.
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