3d compton effect

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Hindawi Publishing CorporationInternational Journal of Biomedical ImagingVolume 2007, Article ID 92780, 11 pagesdoi:10.1155/2007/92780

Research Article

The Mathematical Foundations of 3D Compton ScatterEmission Imaging

T. T. Truong,1 M. K. Nguyen,2 and H. Zaidi3

1 Laboratoire de Physique Theorique et Modelisation, CNRS UMR 8089, Universite de Cergy-Pontoise,2 Avenue Adolphe Chauvin, 95302 Cergy-Pontoise, France

2 Laboratoire Equipes de Traitement des Images et du Signal, CNRS UMR 8051, Ecole Nationale Superieure de l Electroniqueet de ses Applications, Universite de Cergy-Pontoise, 6 Avenue du Ponceau, 95014 Cergy-Pontoise, France

3 Division of Nuclear Medicine, Geneva University Hospital, 1211 Geneva 4, Switzerland

Received 27 September 2006; Accepted 20 February 2007

Recommended by Zhaotian Zhang

The mathematical principles of tomographic imaging using detected (unscattered) X- or gamma-rays are based on the two-dimensional Radon transform and many of its variants. In this paper, we show that two new generalizations, called conical Radontransforms, are related to three-dimensional imaging processes based on detected Compton scattered radiation. The first class ofconical Radon transform has been introduced recently to support imaging principles of collimated detector systems. The secondclass is new and is closely related to the Compton camera imaging principles and invertible under special conditions. As they arepoised to play a major role in future designs of biomedical imaging systems, we present an account of their most important prop-erties which may be relevant for active researchers in the field.

Copyright 2007 T. T. Truong et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. INTRODUCTION

During the last fifty years, progress in imaging systems usingpenetrating radiation for biomedical purposes has broughtabout new topics in mathematics and fueled intense researchactivities with far reaching results. The mathematics of imag-ing science has evolved to a full fledged discipline [1]. Trans-mission computer assisted tomography (CAT-scanning) isbased on an integral transform in two dimensions discoveredin the sixties by Cormack [24], who did not realize that J.

Radon had already introduced and studied it in his seminalpaper [5] in 1917. Subsequently, in an effort to reconstructdirectly in three dimensions an object without having to as-semble its two-dimensional sections, one is led to considerthe so-called X-ray transform or cone beam transform. Thistransform is an off-spring of the Radon transform and mapsa function in R3 to its (straight) line integrals inR3. One wayto reconstruct an object is to convert the line data into planardata in R3 using the Grangeat technique [6]. Then applica-tion of the inversion formula of the three-dimensional Radontransform [7] yields the answer. A further generalization ofthe Radon transform in emission imaging, called the atten-uated X-ray transform, accounts for the radiation loss in the

traversed medium. The problem of its inversion has been amathematical challenge for decades and has been solved onlyin 2001 [8], thanks to complex analysis methods applied tothe stationary photon transport problem [9]. The success ofthis branch of mathematics, coined by Gelfand as integral ge-ometry, goes far beyond the imaging science scope as it hasbrought significant progress in group representation theory,partial differential equations, boundary value problems, andso forth [7].

The standard Radon transform and its variants are re-

lated to a process of data collection in an interaction freepropagation of radiation through matter, possibly affected byattenuation. Thus, radiation energy is not altered from emis-sion to detection. However, a sizable part of traveling radia-tion does suffer an interaction with matter through Comp-ton scattering [10]. Generally as the data quality is lowered,Compton scattering effects have been treated as noise andmust be eliminated. So far, in most image processing meth-ods, the aim is to deal away with it, for example, by fil-tering or by geometric rejection using an antiscatter gridof miniature lead septa. In conventional projection imag-ing, most of the radiation have been scattered in the patientbody, the scatter-to-primary ratio can be as high as 10 [10].


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2 International Journal of Biomedical Imaging

But throwing out all the scattered radiation may not be asmart move since this also means a loss of sensitivity and cer-tainly a loss of valuable information.

This is why we have recently advocated the use of scat-tered radiation to improve quality in image processing [11]as well as to construct new imaging principles [12]. This pro-

posal generalizes the concept of a Compton camera, pro-posed by several workers some thirty years ago [1315], inwhich the idea of electronic collimation is implemented.When radiation is detected at a lower energy than the orig-inally emitted energy, there must be at least one Comptonscattering occurring along its propagation path. But the vastmajority of scattered radiation is due to mainly single scat-tering events [16]. To an emerging ray detected at a definiteenergy there corresponds an ensemble of incoming rays dis-tributed on a circular cone of definite opening angle. Themeasured data consisting of collected emerging radiation atsome detection point is viewed as the integral contributionof a source function on specific circular cones; it may be also

called a conical projection of the source. The name of conicalRadon transform is attributed to such integral transform andis added to the list of already known Radon transformson ge-ometric manifolds inR3: paraboloids [17], spheres [18], spe-cial surfaces [19], second-order surfaces [20], and so forth.Other proposals for use of scattered radiation in X-ray imag-ing which do not rely on conical projections have been madeindependently by [21].

Thus, the main topic addressed here is the mathematicalframework defining the working principles of a new imag-ing technique. To keep the discussion transparent, we haveadopted an ideal working assumption whereby attenuationis not taken into account. A well-known difficulty is that the

nonuniform attenuation along the radiation path leads totremendous mathematical complication. For a given projec-tion, attenuation correction factors in SPECT rarely exceed10 in virtually all clinical imaging situations [22]. An exactsolution is beyond the scope of the present study. It shouldbe pointed out that, in the case of the attenuated X-ray trans-form in emission imaging, a comprehensive analytic solu-tion has been attained only recently [9]. Therefore, in prac-tical situations standard corrections for photon attenuationshould be envisaged.

In conventional emission imaging, the data collected forobject reconstruction is formed by linear projections (conebeam projections) of unscattered radiation filtered by an en-

ergy acquisition window which has already discarded from70% to 80% of the incident photon flux. Moreover, amongthe retained some have suffered scattering in the collimatorand hence must be discarded. It has been reported that col-limator scatter increases as the energy of the photopeak ofinterest increases from a low of 1.9% for Tc-99 m (141 keV)to a high of 29.4% for I-131 (364 keV) with the usual high-energy collimator. The penetration percentage also goes upwith energy. Therefore, correction for photons that penetratethrough, or scatter in, collimator septa is hardly important atall for Tc-99m tracers [23].

In the proposed imaging technique, data for reconstruc-tion are provided by the so-called conical projections, which

gather radiation from point sources lying on large surfacesinside the emitting object. Although contamination of thescatter component by multiple scatter events may be as highas 30% of the total scatter according to Monte Carlo investi-gations [16, 24], we believe that the signal of single scatteredradiation is largely sufficient to make the new imaging prin-

ciples work, in particular when advanced semiconductor-based detectors with better energy and spatial resolution andsensitivity will become available. These interesting issues willbe explored in future work.

In this paper, we present a unified treatment of coni-cal Radon transforms relevant in emission imaging by scat-tered radiation. In fact, we will be concerned with two classesof conical Radon transforms originating from image forma-tion by Compton scattered radiation on a gamma camerawith and without collimator. The first class of conical Radontransform uses circular cone sheets with fixed axis direction(C1-cones) whereas the second class deals with circular conesheets with axis swinging around a point (C2-cones). Note

that if this point goes to infinity in a given spatial direction,then the C2-cone goes over the C1-cone. In each case, we willstart by showing how the image formation process leads toan integral transform and how this transform is related tothe conical Radon transforms. Each conical transform willbe introduced and its relevant properties for imaging pur-poses, in particular their invertibility, discussed. Conclusionsand perspectives are given in the last section.

2. NOTATIONS

Let f be a real nonnegative integrable, smooth, with com-pact support function on R3. The same function in cylindri-

cal (spherical) coordinates is noted f(f).The definitions of various transforms of f(x, y, z) are asfollows:

(i) fi: Conical Ci-Radon transform of f, i = 1,2;(ii) Fj : j-dimensional Fourier transform of f, j = 1,2,3.

Special functions [25] are as follows:

(i) Y(x): Heaviside unit step function;(ii) jl(kr): spherical Bessel function of order land variable

(kr);(iii) Pl(cos ): Legendre polynomial of order land of vari-

able cos ;(iv) Yl,m(k): spherical harmonic (l, m) with argumentk,

solid angle in the direction of the unit vector k.

3. WORK SETTING

In this article, we consider the emission imaging problem,that is, the problem of reconstructing in R3 a gamma-rayradiating object from its Compton scattered radiation data.This object is described by its activity volume density func-tion f. Detection of scattered radiation is performed by agamma camera in two instances: with or without collimator.The recorded data consists of the coordinates of the detectionsite, the surface flux densityof photons at this site (pixel), andthe value of their energy (list mode). Between the radiating


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T. T. Truong et al. 3

Object

Scatteringmedium

Detector

Collimator

Figure 1: Two imaging modalities using scattered radiation with and without collimation.

object and the detector stands a scattering medium: it maybe a volume or a layer as illustrated byFigure 1. Note that the

object itself may also be a scattering medium, and for pho-ton energies above 25 keV, over 50% of the interactions inbiological tissues are scatterings [26]. Higher-order scatter-ing events (of much lower probability of occurrence) will bethe object in future studies.

3.1. Compton scattering

As Compton scattering plays a key role, we will recall someof its properties. The Compton effect discovered in 1923 [27]had served to confirm the particle (photon) nature of radi-ation, as proposed by A Einstein. Thus, energetic radiationunder the form of X- or gamma-rays behave like particles

and scatter with electrically charged particles in matter. Inbiomedical domains, X- or gamma-photons scatter electronsin the biological media they traverse. This scattering processhas cylindrical symmetry around the direction of the incom-ing photon and the energy of the outgoing photon is givenby the Compton formula [28]

E = E0 11 + (1 cos ) , (1)

where is the scattering angle as measured from the incidentphoton direction, E0, the photon initial energy,

=E0/mc2,

and mc2 the rest energy of the electron. Equation (1) showsthat single-scattered photons have a continuous energy spec-trum in the range E0/(1 + 2) E E0.

Thus an emerging photon with an energyE in a directionof unit vector n may originate from an incoming photon ofenergyE0 emitted from a site on a sheet of a circular cone ofaxis direction n and an opening angle .

3.2. Compton differential cross-section

At a scattering siteM, the number of particles d2Nsc scatteredin a solid angle dsc along a direction making an angle with the incident direction follows from the definition of the

differential scattering cross-section (see Figure 2)

dCd , (2)

when the following quantities are given:

(a) in, the incident photon flux density,(b) ne(M)dM, the number of scatterers (electrons) around

the scattering site M with volume dM.

We have

d2Nsc = inne(M)dM

dCd

dsc. (3)

The Compton differential cross-section has been computedin 1929 by Klein and Nishina [29]. It appears as the product

of the area of a disk of radius re, the classical radius of theelectron, and a probability factor P(), that is,

dCd

= r2e P(), (4)

where re = 2.82 1015 m and

P()= 12

11 + (1cos )2

1+cos2 +

1cos2

1+ (1cos )

.

(5)

Thus, we see that, for a given incident energy, the angulardistribution of scattered photons is no longer isotropic [28].

Hence, the final form of this number of scattered photonsin the direction given by the angle is

d2Nsc = inne(M)dMr2e P()dsc, (6)

this number is basic to the image formation by scattered ra-diation.

3.3. Conical projections

In standard computer assisted tomography (CAT), the datais gathered under the form of line projections or integralsof a function (attenuation or activity) along straight lines.


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dsc

M

in

Figure 2: Compton scattering differential cross-section.

(a) (b)

Figure 3: Illustration of linear and conical projections.

Here following the scattering mechanism, the data would ap-pear as conical projections or integrals of a function f on acircular cone sheets. The integration is carried out with theLebesgue measure of the cone in a chosen coordinate system.The result is a function of

(i) the coordinates of the cone vertex,(ii) the parameters of the unit vector of the cone axis,

(iii) the opening angle of the cone, that is, the scatteringangle.

Figure 3 displays the representations of line projectionand conical projection. In the text we will have two types ofconical projections corresponding to the two cases of image

formation mentioned earlier. The question is now how to usethe conical projections to reconstruct the source function f.We will treat the two cases separately in the coming sections.

4. THEC1-CONICAL RADON TRANSFORM

In this section, we consider the possibility of imaging a three-dimensional object by collecting data on its scattered radi-ation on a gamma camera equipped with a collimator andshow how the C1-conical Radon transform arises. Figure 1shows the experimental arrangement with the location of theradiating object, the scattering medium, and the collimatedgamma camera.

4.1. Image formation in gammaimagingby scattered radiation

To concentrate on the scattered imaging principle, we makesome simplifying assumptions [12, 30]:

(1) absence of attenuation for the propagating radiation,

(2) constant density of the electrons ne in the scatteringmedium,

(3) isotropic emission from original radioisotopes in ob-ject.

To compute the photon flux density at a detection site(pixel) D on the collimated camera we start from (6). Radia-tion is emitted at point source S, will propagate to scatteringsite M and reach detection site D.

The incoming photon flux density in on scattering siteM is now computed from the emission data from pointsource. Let f(S)dS be the number of gamma photons emit-ted per unit time by a volume dS in the object around site S.The emission being isotropic, the number of photons emit-

ted in the direction SMin a solid angle dS is

f(S)dS

4dS. (7)

Therefore, the incoming photon flux density at scatteringsite M is

f(S)dS

4

1

SM2= in, (8)

where SM= |SM|.Next, the number of scatterers around site M in a volume

dM

is ne dM

. The net number of photons emerging from thescattering is

f(S)dS

4

1

SM2ne dMr

2e P()dM, (9)

this means that the detected photon flux density at site D is

f(S)dS

4

1

SM2ne dMr2e P()

1

MD2. (10)

Now, all the contributing point sources S, for given scat-tering center M, lie on a circular cone sheet of axis identi-

fied withMD and opening angle , thus we must integrate

with the measure (cone)dS

first. Next, we must take intoaccount all the scattering sites in the scattering medium sit-uated on the line parallel to the collimator axis at site D.Hence, we must perform a second integration with the mea-sure (line)dM. To sum up the detected photon flux densityat D is

g(D, ) =

(cone)f(S)dS

4

1

SM2ne dMr

2e P()

(line) 1MD2

.

(11)

In the cylindrical coordinate system ofFigure 4, the inte-gration measure on the cone is rsin dr d and the measure


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z

x

yO

S

M

D

Figure 4: C1-cone and C1-conical Radon transform definition.

along the line is simplydzM, (11) becomes

g(D, ) =r2e P()ne4

rsin dr d

fxD + rsin cos , yD+ rsin sin , zM + rcos

dzMz2M

.

(12)

Remark 1. In practice as f and ne are volume densities, tokeep the physical dimensions right, we should think of thecone sheet as having a small thickness e and the line onwhich M moves as having a tiny section s. These are con-stants and donot affect the mathematical reasoning, they will

be dropped for the sake of expression simplicity, but shouldalways be kept in mind.

Clearly this imaging equation is a compounded integraltransform. Assuming that integration interchange is valid, ifwe define the first integral transform as

h

xD + rsin cos , yD + rsin sin , rcos

=

dzMz2M

f

xD + rsin cos , yD

+ rsin sin , zM + rcos

,

(13)

we see that the imaging equation (12) is just a conical pro-

jection of the function h on the C1-cones with vertex on theplane xOy.

Let us define an interaction factor which also includes eand s:

K() = r2e P()ne4

es, (14)

then (12) reads

g(D, )

K()=

rsin dr dh

xD + rsin cos , yD

+ rsin sin , rcos

,

(15)

or in terms of our notations (see Section 2)

g(D, )

K()= h1xD, yD, . (16)

4.2. Properties of theC1-conical transform

The C1-conical Radon transform has been discussed in [31],where some of its properties have been studied. However, theproblem of inversion will be handled here with a new ap-proach. We will not go through the method of decomposi-tion of functions in circular components but will show thatthere exists a variant of the central slice theorem [28] whichprovides the grounds to invert the transform as it is done inthe standard Radon transform [28].

First, we observe that by definition in the chosen cylin-drical coordinate system the C1-conical Radon transform off, the cones having vertex on the xOyplane, is

f1xD, yD, = rsin dr dfxD + rsin cos , yD+ rsin sin , rcos

.

(17)

This can be rewritten under the form of a Fredholm in-tegral equation of the first kind with a delta function kernelconcentrated on the sheet of a circular cone [31]

f1xD, yD, =

dxdydzK1

xD, yD, | x, y, zf(x, y, z),

(18)

with

K1

xD, yD , | x, y, z

=

cos

x xD

2+y yD

2 zsin .(19)

We use now the Fourier representation of the delta func-tion

cos

x xD

2+

y yD

2 zsin

=

d exp2i

cos

x xD2 + y yD2 zsin

,

(20)

and the two-dimensional Fourier transform of f(x, y, z),

f(x, y, z) =

dpdqe2i(px+qy)F2(p, q, z). (21)

We can perform the integration over z, which restoresa three-dimensional Fourier transform F3(p, q, r) of f and


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yields a new form of f(xS, yS, ),fxS, yS,

=

dxdy

d exp2i

cos

xxS2

+yyS

2

dpdqe2i(px+qy)F3(p, q, sin ).(22)

Let F2(p, q, ) be Fourier component with respect to thecoordinates xS and yS of f(xS, yS, ), then

F2(p, q, ) =

dF3(p, q, sin )

dxdyexp2i

cos

x xS

2+y yS

2+p

x xS

+ qy yS

.

(23)

The last integral of (23) can be computed using polar co-ordinates in (x, y) a nd (p, q) spaces, that is, (xxS) = cos,(y yS) = sin, dxdy = dd, and p = k cos ,p = k sin , kdkd. Therefore,

dxdyexp2i cos

x xS

2+y yS

2+p

x xS

+ qy yS

=

dde2i[ cos+k cos()].

(24)

Integration on yields a Bessel function of order zero inthe last integral of (24):

dde2i[ cos+k cos()]

=

0 de2i cos2J0(2k).

(25)

Thus, in two-dimensional Fourier space, the C1-conicalRadon transform appears as

F2(p, q, ) =

d

0

d2J0

2

p2 + q2

F3(p, q, sin )e2i cos .(26)

Now, we perform the integration on which brings backthe three-dimensional Fourier transform of f,

dF3(p, q, sin )e

2i cos = 1sin

F2(p, q, cot ).

(27)

This step reduces the C1-conical Radon transform to aHankel of order zero:

sin F2(p, q, )=

0 d2J0

2

p2 + q2

F2(p, q, cot ).

(28)

To perform the inversion of this Hankel transform, weshould switch to an appropriate variable, that is, = cot .But care must be exercised as far as the range of is con-cerned. We will distinguish two cases.

(a) 0 < < /2, then > 0 as well as tan > 0 and (28)can be rewritten as

sin cot2 F2p, q, < 2

=

0 d2J0

2tan

p2 + q2

F2(p, q, ).

(29)

(b) /2 < < , then < 0 as well as tan < 0 and (28)can be rewritten as

sin cot2 F2p, q, > 2

=

0

d2J02tan p2 + q2F2(p, q, ).

(30)

Application of the Hankel identity [25]

1

k(k k) =

0

r dr2Jl(2kr)2Jl(2k r) (31)

leads to the inversion of the Hankel transforms and yieldsthe three-dimensional Fourier components of the object f.

As the dual variable to is

p2 + q2, with = tan , we get

F2(p, q, ) =p2 + q2

0

d2J0

2tan

p2 + q2

1||1 + 2Y2 F2p, q, < 2+Y

2

F2p, q, > 2

.

(32)

Hence, f can be recovered by inverse three-dimensionalFourier transform.

Remark 2. In order to reconstruct the object by inverting thecompound integral transform given by (12), we need to in-vert (13). This is quite easy since it can be viewed as a convo-lution in the variable zD between the two functions 1/z

2D and

f(. . . , . . . , zD + rcos ). As this operation is not important tothe topic of this paper, we refer the reader to [12, 30].

5. THEC2-CONICAL RADON TRANSFORM

5.1. Compton camera

That Compton effect which has been proposed as mecha-nism for imaging is known ever since the fifties. However,there are many ways to do the experimental setups. Most pro-posals are systems with collimated point source and point-like detector, see, for example, [21]. In fact the Compton ef-fect is used to probe the electron density of matter and ap-plied often to nondestructive material control. Here we are


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O

S

M

D

Detector

Scatteringlayer

l

Figure 5: Principle of a Compton camera.

interested in data collected by a gamma camera. In the pre-vious section we have examined the case of a gamma camerawith a lead collimator which has the disadvantage of reject-ing many of the scattered photons. So to improve drasticallydetection sensitivity, the idea of a Compton camera has beenproposed as early as 1974 by many workers [1315, 32].

The concept of a Compton camera is analogous to thescheme ofSection 4 except that the scattering medium is nowa thin scattering layer parallel to the face of a gamma camerawithout collimator. The data consists ofC2-conical projec-tions, the cone sheet axis converging to the detection site D;see Figure 5. Note that when D in a given direction werecover the C1 cones.

Following the image formation process in a Comptoncamera, we will show how a new conical Radon transform,the C2-Radon transform, comes up and sketch a proof ofits invertibility under specific conditions. The true conicalRadon transform of a Compton camera is not yet an ana-lytical inversion formula.

5.2. Image formation by scattered radiationin Compton camera

The radiating object stands above the first scattering layer. Itsprimary rays hit the scattering layer and will be absorbed bythe planar camera (see Figure 5). If only photons of energy

E below the energyE0 of the primary photons are recorded,then each detection site collects all possible conical projec-tions coming from all directions in half space, delimited bythe photon absorbing detector. This is the principle of elec-tronic collimation which has been designed to improve sen-sitivity of gamma cameras.

To reconstruct an object described by a source functionf(x, y, z), we need a set of data consisting of conical projec-tions depending also on three variables. Ideally one couldselect one detection site D, and consider all the projectionsalong circular cones of opening angle and axis swingingaround D but with cone vertex constrained to be on a plane.With these conditions a conical projection will depend on

three parameters: the scattering angle and the two coor-dinates of the cone vertex on the scattering plane. Thus, weobtain a mapping of f onto a function of three variables. Theinverse mapping, when explicitly worked out, would yield acorrect imaging procedure by a Compton camera.

Following the assumptions of Section 4.1, the photon

flux density at detection site D is evaluated in the same man-ner as for the case with collimator:

g(D, ) =

e(cone)f(S)dS

4

1

SM2

ne dMr2e P()s(line)1

MD2.

(33)

Now in the chosen coordinate system (see Figure 5), ithas the expression

g(D, ) =K()

(cone)f(S)dS1

SM2

dxM dyM1

l2 + x2M + y2M,

(34)

lbeing the distance OD, the explicit integration on the conesheet (cone)dS will be given later in Section 5.3 since it isrelated to the C2-conical Radon transform we will be exam-ining.

Up to now there exists only a few attempts to exactly solvethis inversion problem. Cree and Bones [33] were the firstto consider conical projections on a Compton camera whichstill has a collimator. Later on Basko et al. [34] aswell asParra[35] have designed inversion techniques based on propertiesof spherical harmonics as they consider conical projectionsas made up of cone beam projections, but have not touch

really upon the problem of converting cone beam data intoconical projection data, a problem similar to the one solvedby Grangeat [6] for planar projections in R3. There are nu-merous approximate reconstruction methods, most of themusing some back projection techniques (or numerical algo-rithms) and search for point sources as intersections of conesheets reconstructed from coincidence measurements on theCompton camera. Lastly let us also cite some other originalapproaches based on statistical physics [36] as well as alge-braic methods [3739].

In this situation, it is of interest to find an analytic in-version of the specialC2-conical Radon transform responsi-ble for the imaging process in Compton camera. Before tack-

ing this problem, we discuss here a more general problem inwhich the vertex of the scattering cone is not constraint to lieon a plane (or a surface) as in the Compton camera case. Thiswould give us some freedom to find an inversion formula foranother class ofC2-conical Radon transform. We will comeback to the Compton camera in another work. Thus, themathematics of the Compton camera imaging process haveled to a new class of conical Radon transform.

5.3. Properties of theC2-conical Radon transform

The C2-cone is generated by the rotation of a straight linemaking an angle around an axis direction n and meeting


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z

x

y

S

M

D

un

k

Figure 6: C2-cone and C2-conical Radon transform definition.

this axis at vertexM; see Figure 6. Thus, D being the detec-

tion point, we haveDM= M = pn. Let S be a running point

of the cone sheet and denote this point byDS = S = rk. Let

the angle be defined by (k n) = cos . Thus, by consid-ering trigonometric relations in the triangle DMS, one canwrite down the relation

r= p sin sin( ) = p

sin

sin

cos1(k n)

, (35)

which may be regarded as the cone equation in a meridiansection within polar coordinates (r, ) and polar axis n. At = /2 we recover the equation of a plane as a degeneratecone [28].

When evaluating a C2-conical projection, we integrate anonnegative function f on one sheet of the cone. This isequivalent to saying that, giving a mass density, we com-pute the mass of a piece of cone surface limited by theintersection curve of the support of f with the cone. Thismass may be calculated in any convenient coordinate sys-tem.

We will use the coordinate system which is expressed in(35). The area element of the cone is the product of the arc

element of the line by the element of circle in a plane perpen-dicular to the cone axis.

The arc element is

ds =

(dr)2 + (r d)2 = p sin sin( )

d

sin( ) . (36)

Now the element of circle is rsin d. Hence, the conearea element is

da = rsin d p sin sin( )

d

sin( )

= sin d

p sin

sin( )2 d

sin( ) .(37)

In the same coordinate system, a C2-conical projection off is expressed as the integral of f on the cone sheet with theintegration measure da. f has then the expression f(r,k),with k = (, ), r= p sin /sin( ) and angular ranges0 < < and 0 < < 2. Thus,

f2(pn, ) = fp sin sin( ) ,k sin d

p sin

sin( )2 d

sin( ) ,(38)

or alternatively

f2(pn, ) =

f

r,k

r2

r=p(sin /sin())

sin d dsin( ) .

(39)

One may use the integration over a one-dimensional deltafunction to express the substitution ofrby the cone equation(35):

dr

r p sin

sin( )

. (40)

Since

r p sin sin( )

1

sin( ) = p sin rsin( ),

(41)

and r2 drsin d d = r2 dr dk = dS, we can replace theoriginal integration range:

{r R, 0 < < , 0 < < 2}, (42)

by

r R+, = [0 < < < < + ],S

1 = [0 < < 2], (43)which fits in the chosen spherical coordinate system with nas polar axis.

The C2-conical projection of f has now the Fredholmform of the first kind with a delta function kernel. In intrinsicvector notations, it reads

f2(pn, ) = dSf(S)K2(pn, | S), (44)where

K2(pn, | S) = p sin rsin cos1(k n).

(45)

(Compare with the previous case, see (18), (19)).Finally, at = /2 we recover precisely the planar Radon

projection in R3:

f2

pn,

2

=

dSf(S)p r(k n). (46)


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5.4. A central slice-like theorem

Again as in Section 4, we may use the Fourier decompositionof the delta function1

p sin rsin( )

=

d exp 2ip sin rsin( ), (47)together with the decomposition of f into spherical compo-nents

f(x, y, z) = fr,k = l,m

flm(r)Ylmk

, (48)

where, in the chosen spherical coordinate system,k denotesthe direction parameters of the unit vector k. Hence, insert-ing (47) and (48) in (44) we obtain

f(pn, ) =l,m

de2i(p sin )

0r2drflm(r)

S1

dkYlmk

e2irsin().

(49)

Recall cos = (kn). As sin ( ) = cos(/2 + ),we introduce the decomposition of a plane wave in space inspherical components (see [40, page 471]):

e2ircos(/2+)

= n in(2n + 1)jn(2r)Pn cos

2 + ,(50)

where jn(x) is the spherical Bessel function of order n.2

Let u be a fixed unit vector, defined byu, such thatcos(/2 + ) = (k u). Then the Legendre polynomialPn(cos(/2 + )) can be further expanded in terms ofspherical harmonics [25]:

Pn cos

cos

2 +

= 42n + 1

m=nm=n

Ynm

k

Ynm

u

.

(51)

Putting relation (51) in (50) and integrating on dk,since the range of is S1, we can write

S1

dkYlmk

Ynm

k

= mm Kmln (), (52)

1 As thedeltafunctionis an even function, thesign of theexponentialunderthe integration sign may be chosen at will.

2 This is valid for > 0, otherwise we take the Fourier representation of thedelta function with a different sign in (47) as indicated in the previousfootnote.

with |m| < inf(l, n). Thus, the result follows:

f(pn, ) =n,m

Ynmu

de2i(p sin )4i l

0r2 dr

l

jl(2r)Kmln ()flm(r).

(53)

Right-hand side of (53) expresses f(pn, ) as a sphericalcomponent expansion of the C2-conical Radon transform interms of the variable p sin u, instead of pn. So if the C2-conical data can be rewritten under the form of a function ofp sin u and of , with a spherical component decomposi-tion, that is,

f(pn, ) = g(p sin u, ) =lm

glm(p sin , )Ylmu

,

(54)

then we can extract the new data spherical component as

glm(p sin , ) =

de2i(p sin )4i l

0

r2dr

l

jl(2r)Kmln ()flm(r).

(55)

Now by Fourier inverting with respect to q = p sin thetwo sides of (55), (since sin > 0 for 0 < < ), we findthat

sin

dq glm(q, )e2iq

=4i l

0

r2dr

ljl(2r)K

mln ()flm(r).

(56)

Next, by appropriately choosing u, a generalized Hankelidentity may be derived. Recall that for spherical Bessel func-tions (see, e.g., [25]) this identity is of the form

1

k2(k k) =

0

2 d4 jl(2k)4 jl(2k ). (57)

This new identity allows to extract the spherical componentflm(r) of f and thereby achieve inversion (details will be pre-sented elsewhere). Equation (54) relates implicitly p and and may suggest a new type of gamma camera realization,which should be investigated. Finally for = /2, (44) showsthat thisC2-conical Radon transform is just the Radon trans-form in R3. The whole procedure goes through with dras-tic simplifications since the natural choice for u is n, thusf(pn, ) = g(pu, ).

6. CONCLUSIONS AND PERSPECTIVES

The Radon transform has enjoyed tremendous popularity inimaging science as it has been extended, generalized in puremathematics (see, e.g., [19, 41, 42]) as well as exploited inmany fields of applications [17, 43, 44]. In this paper we havepresented two further generalizations of the Radon trans-form, namely, two classes of conical Radon transforms which


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originate from imaging processes using Compton scatteredradiation. The first class, called C1-conical Radon transform,is related to an imaging principle with a collimated gammacamera whereas the second class, called C2-conical Radontransform, contains a special subclass which models theCompton camera imaging process. We have also shown that

inversion ofC2-conical Radon transform can be achieved un-der a special condition which is not yet, for the moment,implemented in gamma-ray emission imaging science. Ex-ploiting scattered radiation to reinforce sensitivity as wellas enlarging field of view and cutting down operating timemay lead to employing large scattering medium but with-out collimator for gamma cameras. The mathematics behindthis perspective will be based on a yet little known Radontransform: the torus Radon transform, which may bring evenmore exciting mathematical topics to be explored in the yearsto come.

ACKNOWLEDGMENTS

This work was supported in part by the French Ministryof Research through Grant ACI/NIM/TRC-2004 (for T. T.Truong and M. K. Nguyen) and by the Swiss National Sci-ence Foundation under Grant SNSF 3100AD-116547 (for H.Zaidi)

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3d compton effect

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