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Radon transform

Radon transform is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Radon transform rather than just read about it. In short: In mathematics, the Radon transform is the integral transform which takes a function f defined on the plane to a function Rf defined on the (two-dimensional) space of lines in the plane, whose value at a particular line is equal to the line integral of the function over that line. The transform was introduced in 1917 by Johann Radon, who also provided a formula for the inverse transform.

Radon transform — main illustration
Radon transform — illustration

Key takeaways

  • Radon transform belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Radon transform to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Radon transform from memory before moving on to harder problems.

Reference excerpt

In mathematics, the Radon transform is the integral transform which takes a function f defined on the plane to a function Rf defined on the (two-dimensional) space of lines in the plane, whose value at a particular line is equal to the line integral of the function over that line. The transform was introduced in 1917 by Johann Radon, who also provided a formula for the inverse transform. Radon further included formulas for the transform in three dimensions, in which the integral is taken over planes (integrating over lines is known as the X-ray transform). It was later generalized to higher-dimensional Euclidean spaces and more broadly in the context of integral geometry. The complex analogue of the Radon transform is known as the Penrose transform. The Radon transform is widely applicable to tomography, the creation of an image from the projection data associated with cross-sectional scans of an object.

Explanation

If a function f {\displaystyle f} represents an unknown density, then the Radon transform represents the projection data obtained as the output of a tomographic scan. The inverse of the Radon transform can be used to reconstruct the original density from the projection data, and thus it forms the mathematical underpinning for tomographic reconstruction, also known as iterative reconstruction. The Radon transform data is often called a sinogram because the Radon transform of an off-center point source is a sinusoid. Consequently, the Radon transform of a number of small objects appears graphically as a number of blurred sine waves with different amplitudes and phases.

The Radon transform is useful in computed axial tomography (CAT scan), barcode scanners, electron microscopy of macromolecular assemblies like viruses and protein complexes, reflection seismology and in the solution of hyperbolic partial differential equations.

Definition Let f ( x ) = f ( x , y ) {\displaystyle f(\mathbf {x} )=f(x,y)} be a function that satisfies the three regularity conditions:

f ( x ) {\displaystyle f(\mathbf {x} )} is continuous; the double integral ∬ | f ( x ) | x 2 + y 2 d x d y {\displaystyle \displaystyle \iint {\frac {\vert f(\mathbf {x} )\vert }{\sqrt {x^{2}+y^{2}}}}\,dx\,dy} , extending over the whole plane, converges; for any arbitrary point ( x , y ) {\displaystyle (x,y)} on the plane, lim r → ∞ ∫ 0 2 π f ( x + r cos ⁡ φ , y + r sin ⁡ φ ) d φ = 0. {\displaystyle \lim _{r\to \infty }\int _{0}^{2\pi }f(x+r\cos \varphi ,y+r\sin \varphi )\,d\varphi =0.}

The Radon transform, R f {\displaystyle Rf} , is a function defined on the space of straight lines L ⊂ R 2 {\displaystyle L\subset \mathbb {R} ^{2}} by the line integral along each such line as:

R f ( L ) = ∫ L f ( x ) | d x | . {\displaystyle Rf(L)=\int _{L}f(\mathbf {x} )\vert d\mathbf {x} \vert .}

Concretely, the parametrization of any straight line L {\displaystyle L} with respect to arc length z {\displaystyle z} can always be written:

( x ( z ) , y ( z ) ) = ( ( z sin ⁡ α + s cos ⁡ α ) , ( − z cos ⁡ α + s sin ⁡ α ) ) {\displaystyle (x(z),y(z))={\Big (}(z\,\sin \alpha +s\,\cos \alpha ),(-z\,\cos \alpha +s\,\sin \alpha ){\Big )}}

where s {\displaystyle s} is the distance of L {\displaystyle L} from the origin and α {\displaystyle \alpha } is the angle the normal vector to L {\displaystyle L} makes with the x {\displaystyle x} -axis. It follows that the quantities ( α , s ) {\displaystyle (\alpha ,s)} can be considered as coordinates on the space of all lines in R 2 {\displaystyle \mathbb {R} ^{2}} , and the Radon transform can be expressed in these coordinates by:

… excerpt ends here. Continue reading the full article.

Illustrations

Radon transform: Radon transform. Maps f on the (x, y)-domain to Rf on the (α, s)-domain.
Radon transform. Maps f on the (x, y)-domain to Rf on the (α, s)-domain.
Radon transform: Radon transform of the indicator function of two squares shown in the image below. Lighter regions indicate larger function values. Black indicates zero.
Radon transform of the indicator function of two squares shown in the image below. Lighter regions indicate larger function values. Black indicates zero.
Radon transform: Original function is equal to one on the white region and zero on the dark region.
Original function is equal to one on the white region and zero on the dark region.
Radon transform: Horizontal projections through the shape result in an accumulated signal (middle bar). The sinogram on the right is generated by collecting many such projections as the shape rotates. Here, color is used to highlight which object is producing which part of the signal. Note how straight features, when aligned with the projection direction, result in stronger signals.
Horizontal projections through the shape result in an accumulated signal (middle bar). The sinogram on the right is generated by collecting many such projections as the shape rotates. Here, color is used to highlight which object is producing which part of the signal. Note how straight features, when aligned with the projection direction, result in stronger signals.
Radon transform: Example of reconstruction via the Radon transform using observations from different angles. The applied inversion to the projection data then reconstructs the slice image.[2]
Example of reconstruction via the Radon transform using observations from different angles. The applied inversion to the projection data then reconstructs the slice image.[2]

Worked examples

Example 1 — a first encounter with Radon transform

Start with the simplest possible case. Write down what Radon transform claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Radon transform before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Radon transform ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Radon transform

In research
Radon transform appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Radon transform in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Radon transform is common in secondary-school and first-year university syllabi. It links to neighbouring topics Integral geometry, Integral transforms, Tomography, so understanding it makes those chapters shorter.
In everyday life
Look for Radon transform outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Radon transform in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Radon transform means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Radon transform out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Radon transform in simple terms?

In mathematics, the Radon transform is the integral transform which takes a function f defined on the plane to a function Rf defined on the (two-dimensional) space of lines in the plane, whose value at a particular line is equal to the line integral of the function over that line. The transform was…

Why does Radon transform matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Radon transform?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Radon transform.

Tags

  • Integral geometry
  • Integral transforms
  • Tomography

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