In this study, we present a technique for improving the reconstruction of optical properties from objects having complex surface geometries. By exploiting patterned illumination for both phase profilometry and optical properties measurements, we were able to achieve large FOV imaging, fast data acquisition, and rapid reconstruction, all with the same instrument. The results are applicable to image-guided surgery, where there is currently no quantitative optical imaging technique used routinely. One application of particular interest is the monitoring of tissue oxygenation status. One could envision extracting optical properties at several wavelengths in order to quantify oxyhemoglobin and deoxyhemoglobin concentration using a modified Beer’s law. This particular application would provide surgeons with the ability to interrogate tissue oxygenation in near real-time.
As briefly stated in the Introduction, co-registration of the acquired images is key in adapting quantitative techniques to relevant in vivo
situations. The two major contributors to co-registration problems are time-related and space-related. Time-related contributions can be further sub-divided into voluntary motions, cyclic involuntary motions due to normal physiological activity (such as heartbeat and respiration), and non-cyclic involuntary motions (due to fatigue, for example). Image acquisition gating, as described previously, can help overcome cyclic involuntary motions (18
). Large voluntary and involuntary motions can be overcome using motion sensors for preventing acquisition during motion. The present study addresses space-related co-registration, independent of time, and can be coupled with image acquisition gating in the future for overcoming both time- and space-related co-registration problems.
In all cases, though, both the number of required images and camera integration time need to be minimized in order to reduce the influence of time-related motions. Our current system, not optimized for fast data acquisition, caused small artifacts due to hand motion. These movements are particularly pronounced in the reduced scattering coefficient maps (), due precisely to the increased AC sensitivity to motion compared to the DC, continuous wave measurements. One of the major potential advantages of the profilometry-based technique we describe is the speed of data acquisition. After initial calibration, only three additional images (i.e., three phases at a single spatial frequency) are required, which depending on fluence rate, camera sensitivity, and camera frame rate, would add only hundreds of milliseconds to data acquisition. Using a multiple cameras imaging system [(37
), Troyan et al., manuscript in review], it should be possible to perform profilometry and optical properties measurements simultaneously, at two different wavelengths, which in turn would improve co-registration even further. Although technically challenging, one might also consider profile-sensitive orientation of the patterned illumination during optical properties measurements, which might reduce acquisition time by half.
However, our technique is not without limitations and room for improvement. We limited calibration and reconstruction to surface height variations of 0 to 3 cm, and tilt angles from ±40°. Indeed, at more extreme angles, the spatial frequency of the projected fringes would decrease dramatically, thus preventing separation of absorption and reduced scattering coefficients during image reconstruction. This is due to the fact that good separation of the DC and AC measurements is necessary, and the AC frequency is typically higher than 0.1 mm−1
for recovery of optical properties. We also noted a tendency for over-correction in reduced scattering and/or absorption coefficients. The origin of this tendency is not yet clear and is presently attributed to many factors. For the angle-dependent correction method, we used a simple cosine to express its Lambertian nature. Other type of dependencies have been reported in the literature (38
), and errors are generated if the model used is not accurate. The spatial frequency broadening due to the projection of a sine wave on an angled surface, while accounted for in our processing by interpolating optical properties as a function of the local spatial frequency, could be more accurately corrected if included directly in the model.
Furthermore, the major source of error in the correction technique we have developed lies in the quality of the phase profilometry data. Small errors in reconstructing surface heights from phase profilometry lead to large angle variations around the true angle value. This was particularly significant in the implementation of the Lambertian reflectance correction. The magnitude of this effect increases dramatically with the magnitude of the true angle value due to the cosine nature of Lambertian reflectance. This results in increased standard deviation in both absorption and reduced scattering coefficients, as seen with the in vivo hand data (). Several possible solutions to this problem exist. First, phase profilometry acquisition could be improved by including additional higher spatial frequencies, which would increase sensitivity to small height changes and reduce random variations of measured surface heights. Second, one could employ a commercially available profilometry analysis package (e.g., from Breuckmann, 3D Digital Corporation, Steinbichler, InSpeck) to acquire the object surface, although these packages tend to be expensive and difficult to integrate into custom instrumentation. Finally, one could perform either time or spatial filtering to reduce noise in the data, although filtering can result in longer acquisition times and/or reduced image quality.