Effects of refraction on tomographic reconstruction

Tony Hyun Kim1, ∗

1Department of Electrical Engineering, Stanford University, Stanford, CA 94305

compiled: March 17, 2013

In practical implementations of tomographic systems, wave phenomena such as refraction represent deviationsfrom the idealized case of straight line tomography. In this paper, a commercial optical design software(Zemax) is used to compute numerically accurate projection integrals along refracted ray paths given arbitrarysource distributions. These “refraction projections” are then fed as inputs to a standard ρ-filter backprojectionalgorithm, and the effect of refraction on the reconstructed distributions is visualized.

1. IntroductionThe basic mathematical problem of tomography is toreconstruct a two-dimensional “source” function f(x, y)given a set of one-dimensional line integrals of f . In suchan idealized tomography set-up, the projections can beconstrued as a representation of f in the basis of linedelta functions, and an elegant mathematical principle– the Projection-Slice Theorem – shows that a perfectreconstruction of f can be performed.

In practice, the various implementations of tomo-graphic measurement and reconstruction violate thestraight line integral assumption of the mathematicalproblem. For instance, in electromagnetic (radio, mi-crowave, optical) or ultrasound tomography set-ups, theline integral measurement is understood to be along theray direction, which will refract or even undergo com-plicated reflections within the sample. In such cases,the path integral will be perturbed from the idealizedstraight line, where the exact perturbation will be ob-ject (i.e. f(x, y)) dependent.

In this paper, we regard refraction as a perturbationto the straight line tomography and evaluate its effects.A novel feature of the current work is the integrationof a commercial optical design software Zemax (RadiantZemax LLC) whose ray tracing engine is used for ac-curate refracted path calculations. (Particularly inter-esting is Zemax’s ability to import arbitrarily complexCAD models of potential tomography targets.) The nu-merical experiment will be as follows: first, we developthe filtered backprojection algorithm for reconstructingf(x, y) assuming straight line integrals; second, we setup the refracted path forward model in Zemax; finally,we use the refracted path projections as the input tothe backprojection algorithm, and compare the resultsto the actual source distribution.

This work is part of an ongoing fascination with the el-egant mathematical problem of tomographic reconstruc-tion. Given that in practice, physical complications such

∗ kimth@stanford.edu

as refraction are always present, it is of great personalinterest to understand how the complications theoret-ically affect the tomography problem and to discoverhigh-performing and/or efficient algorithms for their cor-rection or even take advantage of the additional physics.

2. Basic set-up

In this section, we describe the set-up of the numerical“refracted tomography” experiment, in which we feed re-fracted path length projections as inputs to the filtered-backprojection reconstruction algorithm.

2.A. Tomography geometry

Since we are performing numerical experiments, it isnot absolutely necessary to give explicit physical dimen-

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Fig. 1. Basic dimensions of the numerical tomography setup.The entire workspace is 10 mm× 10 mm. Arbitrary objectscan be inserted at any position into the workspace. Thetransverse intercept of a ray at the exit port is given by t.

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Fig. 2. Demonstration of the standard filtered backprojection algorithm. (a) Forward projection. The left panel shows theboundaries of the original object (based on elliptical primitives) in our tomography workspace. The right panel shows the pathintegral of the object at an offset t along the projection axis. (b) Back projection. Non-filtered (left) and ρ-filtered (right)reconstructions of the original object with projections taken at every 1◦ interval from 0◦ to 180◦. The boundaries of the originalobject are superimposed in white. There is excellent agreement between the reconstructed result and the source distribution,especially for filtered backprojection.

sions to our tomography setup. However, the opticaldesign software Zemax is based on real units (mm) and,for consistency, we will adopt the tomography geometryas shown in Fig. 1. The complete 2-D workspace is a10 mm × 10 mm square in which arbitrary objects canbe placed at any point (as long as it does not intersectthe entrance and exit ports). The transverse interceptof a ray at the exit port is given by t.

Note that the object under test is placed in free space,with an index n = 1. Hence we will subtract the freespace reference of n · d = 10 mm from all path lengthmeasurements.

2.B. Standard filtered backprojection algorithmThe backprojection algorithm for reconstructing thesource distribution f(x, y) from its projections is wellestablished [1]. Fig. 2 demonstrates our implementationof the forward and filtered-back projection routines inMatlab. In Fig. 2(a), the standard geometry for com-puting straight line integrals is illustrated in the spatialworkspace, and a particular projection along θ = 30◦

is shown. Fig. 2(b) shows the reconstructed geometry,using projections at every 1◦ interval from 0◦ to 180◦.The left panel shows the naive, non-filtered backprojec-tion result (for which we expect 1/r blur), while the

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right panel shows the ρ-filtered backprojection result.The boundaries of the original source object is then su-perimposed. There is excellent agreement between thereconstructed distribution and the original source, asexpected for the ideal problem of reconstruction fromstraight line projections.

2.C. Refracted forward-projections with Zemax

Having established the basic ρ-filtered backprojection al-gorithm, our next task is to compute forward projectionsof arbitrary objects with correct refraction. We makeuse of the ray tracing engine of Zemax, accessible fromMatlab via the “MZDDE” toolbox [2].

Our Zemax model of the tomography setup is achievedby using the mixed sequential/non-sequential mode ofthe optical design software. As in Fig. 1, we define a10 mm diameter “entrance port” surface, which acts asthe optical stop for a 0◦-collimated fan of rays that com-prise the projection. These rays propagate towards the“exit port” surface where the optical path length is mea-sured as a function of transverse position t at the exitport. (This arrangement models the experimental setupin which one can place a detector at any known posi-tion on the exit port, but has no a priori knowledgeabout the propagation path.) Between the two ports isa nonsequential object that contains an arbitrary sourcedistribution under study. The targets in this paper weremodeled in Creo Parametric (PTC Inc.) and importedinto Zemax [3]. In the nonsequential mode of Zemax,rays can undergo arbitrarily complex interactions – in-cluding refraction, total internal reflection, polarization-dependent splitting (when enabled), and so on. Fig. 3shows examples of refraction projections, which can besurprisingly complex even for simple objects. All objectshave an index of nobj = 1.05, i.e. 5% variation in indexfrom the background. For the case of the circular andrectangular targets, Fig. 3 also shows, for comparison,the expected projection if the rays were nonrefracting.

There are two phenomena that are apparent in theprojections of Fig. 3 which require special treatment.

2.C.1. Dark intervals at the exit port

First is the phenomenon of “dark intervals” at the exitport. When refraction is taken into account, uniform il-lumination at the entrance port does not guarantee com-plete illumination at the exit port. (In contrast, in thecase of straight line projections, uniform exit port illu-mination is trivially guaranteed.) This phenomenon canbe readily observed in the projection of a circular target(top row of Fig. 3), where the portion of the exit planecorresponding roughly to 1.5 < |t| < 2.5 receives no rays.Dark intervals are problematic for our reconstructionalgorithm since filtered backprojection is conceptuallybased on a convolution of the projection measurementwith a ρ-weighted spatial kernel function.

For the purposes of filtered backprojection in this pa-per, I will apply, rather arbitrarily, cubic interpolationfor the dark intervals in a given projection.

2.C.2. Multipath due to lensingThe second phenomenon that we must resolve is “multi-path” or lensing of the rays. Consider the tilted squaretarget in the second row of Fig. 3. Due to steep refrac-tion and total internal reflection within the target, multi-ple rays can intercept the exit surface at the same height.This means that the optical path length as a function ofexit coordinate t may be multiple-valued when refrac-tion is taken into account. This is clearly a problemfor the reconstruction routine, since our mathematicaloperations are not defined for multiple-valued functions.

When refraction is taken into account, the phe-nomenon of multipath is extremely common. Returningto the circular target of Fig. 3, one might naively expectthat as the input ray approaches the top and bottomedges of the circle, the projected rays would monoton-ically fill the dark intervals noted in Section 2.C.1. Inreality, the rays are refracted more steeply as they ap-proach the edges of the circular target, which results inmultipath in the interval −1.5 < t < 1.5.

Again, for the purposes of this paper, we will adopt asimple (but somewhat arbitrary) protocol for the reso-lution of multiple-valued projections. For any position ton the exit plane, we will take the minimum optical pathlength measurement as the single value of the projectionthat will be backprojected. Note that, in experimentalpractice, one might measure the propagation delay of apulse from entry to exit port as a measure of the ray’soptical path length. In such a protocol, the most obviousfeature of the measurement is likely to be the minimumpropagation delay among the various possible paths.

The last row of Fig. 3 illustrates how the phenomenonof dark intervals and multipath can create extremelycomplicated projection curves for even relatively simpletargets (a tilted Stanford “S”, which has just 22 facets).

3. Sample reconstruction problemsNow that we have discussed the immediate numericalissues posed by refraction, and our methods for theirresolution, we show the results of filtered backprojectionof the targets presented in Fig. 3. The numerical setup ofthe forward projection is as follows. For a fixed rotationfrom θ = 0◦ to 180◦ in 1◦ intervals, we:

1. Launch a fan of Nrays = 5000 rays at the entranceport; compute each ray’s intercept t on the exitport as well as the ray’s optical path length.

2. Bin the exit port intercept into Nbins = 1000 bins.Note that, if the rays were nonrefracting, therewould be Nrays/Nbins = 5 rays per bin.

3. Find the minimum optical path length among therays belonging a particular bin.

4. (Cubic) interpolate path length values for bins thatreceived no rays.

By processing the refracted projection by the aboveprotocol, we obtain a well-behaved function that is suit-able for backprojection. See Fig. 4 for an example of

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Fig. 3. Examples of refracted projection. All object indices are nobj = 1.05. (Top row) A circle of diameter 5 mm. Note thephenomenon of “dark intervals” (1.5 < |t| < 2.5) at the exit surface, which are regions that receive no rays. (Middle row) Asquare of edge length 4 mm. Note the lensing of projection rays caused by refraction and total internal reflection. The opticalpath length as a function of exit surface intercept t can be multiple-valued. (Bottom row) Refraction through a tilted Stanford“S.” Inset shows the level of complexity that can be observed in the path length projections, even with a relatively simpletarget. (The Stanford S logo has just 22 facets.)

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Fig. 4. Processing the raw refracted projection by the proto-col described in Section 3. We take the minimum measuredoptical path length at each t, and interpolate the resultingvalues over the dark intervals.

the above protocol applied to the multi-valued projec-tion through a tilted square (same source configurationas the second row of Fig. 3).

3.A. Circular target

The top row of Fig. 5 shows the backprojection recon-struction of the 5-mm diameter circle, with refractiontaken into account in the forward model. For this sim-ple target, we find that the general extent of the tar-get can be recovered. However, the object boundaryremains non-sharp even with ρ-filtered backprojection.The extent of the remaining blur is likely to be sensi-tive to the choice of interpolation method for the darkintervals. Note that our cubic interpolation for the darkintervals has a gentle taper at the edges of the object,while the “exact” nonrefracted projection will have a“hard”

√1− t2 dependence (i.e. slope not continuous

at object boundary).

3.B. Square target

More interesting is the backprojection reconstruction ofthe 4-mm wide square target, shown in the middle rowof Fig. 5. In both naive and filtered backprojections, wefind that the object does not appear symmetric aboutthe x = 0 plane. This is reasonable, since symmetryabout x = 0 for the ray paths is broken when refractionis taken into consideration. In turn, this implies thatwhen refraction is taken into account a full 360◦ rotationof the target will yield more information than just the0◦ to 180◦ scan.

Note that the edges of the square in the ρ-filtered re-construction appear sharper than their counterparts in

the reconstruction of the circle. This is intuitively plau-sible since ideal (nonrefracting) projections of the squarewill yield linear tapers at the edges, which are well ap-proximated by our cubic interpolation as shown in Fig. 4.(Compare to the nonrefracting projection in the secondrow of Fig. 3.) We are led to the general idea that differ-ent interpolation schemes may be well suited for differentclasses of source objects.

3.C. Stanford “S”The bottom row of Fig. 5 shows the failed reconstructionof the Stanford “S.” The original source is entirely un-recognizable, especially in the ρ-filtered result which ap-pears to be nearly uniform intensity over the workspace.The abysmal reconstruction strongly suggests that thebackprojection algorithm is inadequate for even mod-estly complicated refracting targets.

4. Further workWe have shown that it is possible to utilize a commercialray-tracing engine to model ray-based tomography sys-tems with correct refraction (and reflection) behavior.We have shown that the backprojection algorithm failsfor even modestly complicated refracting targets, suchas the Stanford “S” with its 22 facets. There are manyfurther ideas to pursue.

First, we may try additional targets. If the circulartarget is permissible, while the Stanford “S” is not, itwould be interesting to evaluate the “reconstructability”of refracting targets as a function of their shape complex-ity. (It may be possible to characterize the complexity ofa refracting target, for example, by the RMS deviationof the refracting ray intercepts from their nonrefract-ing intercepts.) Similarly, we may investigate the recon-structability of a fixed shape as a function of varyingindex. Finally, it would also be interesting to examinenon-simple targets, i.e. objects with internal structuresuch as the elongated ellipse in Fig. 2.

Second, the two-dimensional workspace considered inthis paper should be generalized into three dimensions.This is necessary since a ray intersecting an arbitraryobject in the workspace may refract not only within theplane, but possibly also out of plane! When refractionis taken into account, the simple idea of taking a planar“slice” of a complex object is in general not valid.

Finally, given the abysmal performance of the filteredbackprojection method for refracted projection measure-ments, we are left wanting for better reconstruction al-gorithms!

References

[1] Kak, A. C. and Slaney, Malcolm. Principles of Comput-erized Tomographic Imaging, IEEE Press, 1988.

[2] Griffith, D. How to talk to Zemax from MATLAB, ZemaxKnowledge Base.

[3] Nicholson, M. How to import CAD objects, Zemax Knowl-edge Base.

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Fig. 5. Examples of refracted backprojection, using projections at every 1◦ interval from 0◦ to 180◦. All object indices arenobj = 1.05. (Top row) A circle of diameter 5 mm. Note that the object boundaries are not sharp, even under the ρ-filter.(Middle row) A square of edge length 4 mm. Symmetry about x = 0 is broken when refraction is taken into acount. (Bottomrow) Failed reconstruction of the Stanford “S.” The original source is entirely unrecognizable. In particular, the ρ-filtered resultgives almost no information about the source.