In Compton imaging, each event will create a cone with an opening apex angle derived from the Compton scattering formula, known as a Compton cone. The cone's axis is given by the vector connecting the first two interaction positions. The surface of a Compton cone represents the possible original directions of the incident gamma photon. If the incident energy
E0 and the energy loss at the first interaction △
E1 are known, then the opening angle (the Compton scattering angle at the first interaction,
θ1) is represented by:
where
mec2 is the rest mass of the electron.
Actually, there is no priori knowledge of the incident gamma-ray energy in some applications. Therefore, how to estimate the initial energy becomes the key to realize Compton imaging. For a 3-interaciton event which a gamma photon undergoes two successive Compton scatter interactions followed by a third interaction, the energy of incident gamma photon can be calculated. If the interaction positions at the 3-interaction sites are
p1,
p2, and
p3, the energy losses at each detector layers are △
E1, △
E2, and △
E3, and the scattering angle at the first two interaction sites are
θ1,
θ2, then the incident energy
E0 can be calculated as:
However, the efficiency of collecting 3-interaction events is significantly lower. It is necessary to estimate the possible incident energy according to the summation of the observed 2-interaction events. In this paper, the spectral dimension is added to the emission distribution, and it is extended over both spatial domain and energy domain. Thus, each event can obtain the emission energy from any value in the spectral range. Considering that the gamma-ray emission follows a Poisson distribution, the list-mode maximum likelihood expectation maximization (LM-MLEM) [
23] is appropriate for reconstructing the initial energy and spatial distribution of gamma-ray sources through the iterative calculation. Here, the system matrix
tij,E0, presents the probability of an emission from the
jth pixel under incident energy
E0 to be detected as the
ith event. The LM-MLEM algorithm is described as follows:
where λ
j,E0n denotes the image value of pixel
j after
n iterations,
sj,E0 is the sensitivity of the detector for pixel
j. In this paper, the Compton cone of each event is expressed in spherical coordinate system, and the imaging space for Formula (4) is the 2π directional space. Therefore,
sj,E0 is assumed to be uniform in this work. When the source-to-detector distance is large comparing with the detector size, the vertex of each Compton cone is approximately considered to be at the coordinate origin. Under the far-field approximation, the system matrix
tij,E0 is formulated as:
where
pi(
E0) is the probability of the event origins from incident energy
E0,
θi,E0 is the scattering angle calculated from Formula (1),
ω(
θi,E0) is the error weight coefficient related to the scattering angle
θi,E0,
αij,E0 is the angle between the spherical coordinate vector and the Compton cone axis vector,
σ is the Gaussian width of the cone (a constant small value correspond to the uncertainty of the cone angle). The reconstructed result of gamma-ray direction is expressed by polar angle and azimuthal angle (
θ,
φ). In Formula (5),
ω(
θi,E0) and
pi(
E0) are described in detail as:
where
E1,i,
E2,i, σ
E1,i, and σ
E2,i are the deposited energy and Gaussian standard deviation of the first two interactions, respectively. From Formula (7), the system matrix is divided into photoelectric absorption and Compton scattering according to the second interaction. If the scattered gamma photon from the first interaction is fully absorbed at the second interaction, a Gaussian function is used to describe the situation (
E0∈[(
E1+
E2)±3(σ
E1+σ
E2)]). If the second interaction is a Compton scattering and the scattered photon escapes the detector, thus only partial energy of the incident gamma-ray is deposited (
E0>(
E1+
E2)+3(σ
E1+σ
E2)). The term dσ
C(
E0-
E1,i)/dΩ|
E2,i presents the probability that the gamma photon with energy (
E0-
E1) deposits
E2 in the second interaction by Compton scattering, which is predicted by the Klein-Nishina formula.
In the far-field energy-domain imaging method, the spatial reconstruction part is similar to that proposed by Kishimoto A [
3] and Omata A [
21], and the energy domain part is similar to that proposed by Xu D [
24] and Muñoz E [
25]. In order to reduce the burden of matrix calculation in iterative reconstruction, the spatial and spectral imaging space are simplified appropriately. The number of bins in (
θ,
φ) spatial domain is set to 60×60, which means the angle accuracy of each bin is 3°. The number of bins in
E0 energy domain is set to 360, which is an inter-partition distribution covering the energy range of 0 to 8 MeV, as shown in Formula (8).