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Euclidean Radon transform and filtered backprojection — Examples and Counterexamples

1 · Prerequisites

2 · Logical flowchart

3 · Definitions, theorems and proofs

None yet.

4 · Examples, counterexamples and false statements

ExampleConstruction: AI-generatedVerification: AI-generatedjudge pass (gpt-6-luna)verified 2026-10-22 (gpt-6.1-sol)Open item page →

A smooth radial phantom and its sinogram

Example

Define η(u)=0 for u≤0 and η(u)=e−1/u for u>0, and put f(x)=η(1−∣x∣2) on R2. This is a nonzero, smooth, compactly supported radial phantom. Its Euclidean Radon transform is independent of θ and is Rf(θ,s)={∫−1−s21−s2η(1−s2−t2) dt,∣s∣<1,0,∣s∣≥1.

Facts & Assumptions

Given: The function η and the radial phantom f in the Example.

[F1]

The Euclidean Radon transform on R²: Rf(θ,s)=∫Rf(sθ+tθ⊥) dt with θ∈S1 and θ⊥=(−θ2,θ1).

[F2]

A continuous real function on a compact Jordan measurable set is Riemann integrable over that set: continuous real functions on compact Jordan sets are Riemann integrable; use real and imaginary parts for complex integrands.

Verification

1.1givenalgebra

For u>0, repeated differentiation gives η(k)(u)=Pk(1/u)e−1/u for a polynomial Pk. For every integer m≥0, vme−v→0 as v→∞: if v>0, the exponential series gives ev≥vm+1/(m+1)!. Hence each right derivative tends to 0 at u=0, and the quotient η(k)(u)/u also tends to 0 because it is again a polynomial in 1/u times e−1/u. Induction on k shows the zero extension is smooth on R.

2.1givenstep 1.1algebra

The composition f(x)=η(1−∣x∣2) is smooth and radial; it vanishes whenever ∣x∣≥1 and is positive at x=0. Thus it is nonzero and has compact support in the closed unit disk.

3.1F1F2step 2.1∎

For every θ∈S1, orthogonality gives ∣sθ+tθ⊥∣2=s2+t2, so [F1] yields Rf(θ,s)=∫Rη(1−s2−t2) dt. If ∣s∣≥1, then 1−s2−t2≤0 for every t, so the line integral is 0; if ∣s∣<1, the integrand vanishes outside ∣t∣<1−s2 and equals the exponential displayed in the Example inside that interval, with value 0 at its endpoints because η(0)=0. It depends on θ only through the norm identity, so the sinogram is radial-data independent of orientation. The continuous compactly supported integrands are Riemann integrable by [F2].

ExampleConstruction: AI-generatedVerification: AI-generatedjudge pass (gpt-6-luna)verified 2026-10-22 (gpt-6.1-sol)Open item page →

A point source as a distributional Radon limit

Example

Let η(u)=0 for u≤0 and η(u)=e−1/u for u>0, set ψ(x)=η(1−∣x∣2) on R2, let J=∫R2ψ(x) dx, and define ϕ=J−1ψ. For ε>0 put ϕε(x)=ε−2ϕ(x/ε). The functions ϕε are radial smooth unit-mass point-source approximations. For ρ(s)=∫Rϕ(sθ+tθ⊥) dt, which is independent of θ, their full line data satisfy Rϕε(θ,s)=ε−1ρ(s/ε). For each fixed θ∈S1 and every test function h∈Cc∞(R), the offset distributions converge to the point mass: lim⁡ε↓0∫RRϕε(θ,s)h(s) ds=h(0). Thus the point-source sinogram is δ0(s) in the offset variable, for every line normal.

Facts & Assumptions

Given: The functions η, ψ, ϕ, and ϕε in the Example, with J to be shown positive and finite.

[F1]

The Euclidean Radon transform on R²: Rf(θ,s)=∫Rf(sθ+tθ⊥) dt.

[F2]

A continuous real function on a compact Jordan measurable set is Riemann integrable over that set: continuous functions on compact Jordan sets are Riemann integrable.

[F3]

Linearity, monotonicity, the absolute-value estimate and coordinate-slice additivity for the Riemann integral in Rm: the Riemann integral is monotone and additive across coordinate cuts, and linear on integrable functions.

[F4]

Riemann--Fubini on product rectangles, with lower and upper section integrals and content-zero exceptional sections: an integrable function on a product rectangle has equal product and iterated Riemann integrals when its sections are integrable.

[F5]

A compactly supported Riemann integrand admits the global change-of-variables formula from a diffeomorphism near the relevant compact preimage: compactly supported Riemann integrals obey the change-of-variables formula for an injective C1 diffeomorphism with its absolute Jacobian.

Verification

1.1givenalgebra

For u>0, repeated differentiation gives η(k)(u)=Pk(1/u)e−1/u for a polynomial Pk. The exponential-series bound ev≥vm+1/(m+1)! for v>0 shows that each such expression and its difference quotient tend to 0 as u↓0; induction on k proves that the zero extension is smooth. Hence ψ is smooth, nonnegative, vanishes for ∣x∣≥1, and is positive near x=0.

2.1givenF2F3F5step 1.1

By [F2], ψ is Riemann integrable on a bounding rectangle; 0≤ψ≤1 and its support lies in [−1,1]2, so [F3] gives J<∞. On [−1/4,1/4]2 one has 1−∣x∣2≥7/8, hence ψ≥e−8/7; monotonicity in [F3] gives J≥e−8/7/4>0. Thus ϕ is defined, radial, smooth, compactly supported, nonnegative, and has integral one. Applying [F5] to x=εy gives ∫R2ϕε(x) dx=ε−2ε2∫R2ϕ(y) dy=1 for every ε>0.

3.1F1F2F4F5step 2.1

The scaling t=εu in the line integral [F1] gives Rϕε(θ,s)=ε−1ρ(s/ε). Radiality gives ϕ(sθ+tθ⊥)=J−1η(1−s2−t2), so ρ is independent of θ and vanishes for ∣s∣>1. It is continuous: for s′→s, ∣ρ(s′)−ρ(s)∣≤2sup⁡∣t∣≤1∣ϕ(s′θ+tθ⊥)−ϕ(sθ+tθ⊥)∣⟶0, since ϕ is uniformly continuous. Thus ρ is compactly supported and Riemann integrable by [F2]. Riemann-Fubini [F4] and the orthogonal change of variables (s,t)↦sθ+tθ⊥, whose absolute Jacobian is 1, give ∫Rρ(s) ds=∫R2ϕ(x) dx=1.

4.1givenF2F5step 3.1algebra

By step 3.1, ρ is continuous and supported on [−1,1], so Rϕε(θ,⋅)h is compactly supported and continuous. If h is complex-valued, apply [F2] and the compact-support change of variables [F5] separately to its real and imaginary parts; thus with s=εu we get ∫RRϕε(θ,s)h(s) ds=∫−11ρ(u)h(εu) du. Uniform continuity of h on [−1,1] implies sup⁡∣u∣≤1∣h(εu)−h(0)∣→0. Since ρ≥0 and ∫ρ=1 by step 3.1, the integral tends to h(0).

5.1step 4.1∎

The functional h↦h(0) is the point mass δ0 by definition of the Dirac distribution. Step 4.1 proves the asserted distributional limit for every fixed normal θ.

ExampleConstruction: AI-generatedVerification: AI-generatedjudge pass (gpt-6-luna)verified 2026-10-22 (gpt-6.1-sol)Open item page →

A finite complete-angle filtered-backprojection calculation

Example

Assume Countable Choice for the continuous backprojection convention. As a finite-grid illustration, take eight equally spaced full-circle directions θj=(cos⁡(2πj/8),sin⁡(2πj/8)), j=0,…,7, four detector offsets sm=m−2 for m=0,1,2,3, detector spacing Δs=1, and the synthetic row Gj=(0,0,1,0) at every direction. Apply the length-four radix-two FFT to each row, multiply frequency k by the declared sampled ramp λk=2πmin⁡(k,4−k)/4, and invert the finite transform. Each filtered row is Q=(0,−π/4,π/2,−π/4). With the eight-point trapezoidal angular rule of weight Δθ=π/4, the one-pixel backprojection at x=0 is f~(0)=14πΔθ∑j=07Qj[2]=π4. This is the exact output of the specified finite computation. The array is a synthetic discrete sinogram; no claim is made that the finite detector or angle grid exactly represents a continuous phantom or that this output converges to one. The continuous theorem assumes full continuous data and makes no finite-sampling, truncation, or noise guarantee.

Facts & Assumptions

Given: The finite array and quadrature convention in the Example, Countable Choice, and the recursive radix-two FFT on length four.

[A1]

Countable Choice, written ACω, means every sequence of nonempty sets has a choice function. (The Axiom of Countable Choice (ACω))

[F1]

Complete-data filtered backprojection: take the negative-sign 2π Fourier transform in detector offset, multiply by 2π∣σ∣, inverse transform, backproject over the full circle, and scale by 1/(4π).

[F2]

The recursive radix-two fast Fourier transform: FFT⁡m is the recursive even/odd transform on arrays of length 2m.

[F3]

Correctness of the recursive radix-two FFT: for every length 2m input, FFT⁡m returns the unnormalised engineering DFT.

[F4]

The unnormalised engineering DFT and its conversion to the unitary transform: Xk(G)=∑m=0N−1Gme−2πikm/N and Gm=N−1∑k=0N−1Xk(G)e2πikm/N.

[F5]

Finite Fourier inversion for the unitary transform on Z/NZ: the finite inverse transform has positive sign and factor N−1/2 in the unitary convention; after the engineering rescaling the inverse formula has factor 1/N.

Verification

1.1givenF2F3F4algebra

The only nonzero detector sample is at m=2, so the engineering DFT is Xk=e−2πik(2)/4=(−1)k. By [F2] and [F3], the length-four radix-two FFT returns X=(1,−1,1,−1). The sampled ramp is λ=(0,π/2,π,π/2), hence its filtered frequency array is Y=(0,−π/2,π,−π/2).

2.1F4F5step 1.1algebra

The inverse formula [F4] gives Qm=14∑k=03Yke2πikm/4. For m=0,1,2,3 the sums are respectively 0,−π,2π,−π, so Q=(0,−π/4,π/2,−π/4).

3.1givenA1F1step 2.1algebra∎

At x=0, the detector coordinate is s=0, which is bin m=2 for every direction. Therefore the declared angular quadrature and backprojection scale give f~(0)=14ππ4∑j=07Qj[2]=14ππ4(8)(π/2)=π/4. This verifies the displayed finite output only; no equality with a continuous source value is used.

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