A visible wide field multispectral system for comprehensive imaging of skin chromophores and blood vessels has been implemented, and an inhomogeneous Monte Carlo model of photon migration with randomly distributed blood vessels embedded in dermis has been developed. Predetermined nonlinear transforms have been obtained to address the nonlinear interdependent relationship among diffusive reflectance spectra, skin physiology properties, and geometry. For validation, in addition to real skin experiments and phantoms experiments, two alternative methods for blood vessel imaging have been used on the same set of subjects to compensate for the lack of ground truth for skin subsurface imaging.
Humanitarian landmine detection and clearance is one of the most challenging, difficult and time-consuming tasks to be completed with existing technologies. Infrared (IR) Imagery has been used to find differences in heat transfer on the surface of the soil due to a buried object. In this paper, we will describe a method, Dual Frequency Microwave Enhanced Infrared Thermography (MEIT). Heating with microwaves instead of natural sunlight leads to a number of advantages, such as more efficient heating to enhance the thermal signature, and the ability to sense electromagnetic as well as thermal properties of the buried object. However, like other IR techniques, it is limited by surface roughness. Thus, the two frequency technique is used to minimize the clutter introduced by the rough, irregular surface of the ground itself, and vegetation covering the ground. The dependence of scattered waves on frequency is weak enough to makes this possible. A 2-D computational model of this method has been developed to simulate real-world landmine detection. Moreover, ROC (Receiver Operating Characteristic) curves are used to evaluate the performance of the system applying this method.We have previously presented analytical and experimental results on Microwave-Enhanced Infrared Thermography. In [1] [2], we have shown that using microwave heating of the ground can produce strong enhancements of the infrared signature of the shallow-buried objects, while diurnal variation of the heating pattern, caused by natural sunlight, is much weaker. Moreover, we have described how different signatures impart electromagnetic and thermal information in [3].In all the above work, analysis and results are based on an ideal uniform interface at air-ground boundary, say, a flat smooth surface. Furthermore, we have shown that the effects of surface roughness produce clutter, which masks the signals from buried objects in [4] [5]. As surface roughness increases, infrared signatures of buried objects becomes more unreadable and have an increasing probability of producing false alarms due to hot spots on the surface generated by local variation in surface orientation.For detecting landmines and discriminating between landmines and other buried objects, this effect also increases the difficulty of the following image-processing procedure to exact information out of the obtained heating pattern.
A catheter-based near infrared spectroscopy (NIRS) system has recently been cleared by the FDA for detection of lipid core containing plaques of interest (LCP) and lipid core burden index (LCBI) in patients undergoing coronary arteriography. NIRS data are plotted as a map (chemogram) of pullback distance versus rotation, with yellow indicating lipid (see below). Analyses for LCP were based on a 2mm block chemogram and LCBI. An algorithm has been developed to perform automated enhancement of the chemogram and facilitate calculation of the number of LCPs (nLCP) in a segment of artery. The goal is to determine if the enhanced algorithm performs as well as the previously validated LCP and LCBI measures, as determined by histology in human coronary autopsy specimens. NIRS data were obtained from 181 segments from 78 hearts and compared with histology at 2 mm intervals. The image analysis was applied to the chemogram and the nLCP calculated. The ROC analysis of the nLCP versus presence of fibroatheroma in each segment yielded an AUC of 0.84 (95% CI 0.77– 0.89). When one or more LCP was detected, 87% sensitivity and 70% specificity were observed for detection of fibroatheroma. The Spearman correlation between nLCP and LCBI was 0.83 (p-value ≤0.0001). The correlation coefficient of nLCP between repeat pullbacks was 0.83 (p-value ≤0.0001). The number of NIRS-detected LCP in chemograms identified with image enhancement correlates well with previously validated measures and the presence of fibroatheroma by histology. This method has the potential to enhance the clinical utility of the chemogram.
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