How Does SPECT Create an Image?

If you have ever looked at a SPECT scan, it is easy to assume the camera simply “takes a picture”... Spoiler alert, it does not.

In fact, a SPECT image is reconstructed from multiple individual measurements collected as the gamma camera rotates around the patient. Understanding that process is one of the biggest "eureka!" moments in nuclear medicine imaging.

Let’s build that intuition.

Step 1: The camera never sees the whole picture

Imagine a small radioactive source inside the body.

As the gamma camera rotates, it only measures how much activity lies along each viewing direction. Each measurement is called a projection.

Think of shining a flashlight through an object and recording only the shadow but not the object itself.

After one projection, we still do not know exactly where the radioactivity is. But after multiple projections from different angles, we have enough information to reconstruct the image.

The gamma camera records a different two-dimensional projection at each viewing angle.

Step 2: The sinogram

This is where things become interesting.

Instead of displaying each projection separately, we stack them one on top of the other; This is what we call a sinogram.

At first glance, a sinogram does not look anything like an anatomical image. It appears as a collection of curved lines, but those curves are not random.

Every bright point inside the patient traces out a smooth sinusoidal path as the camera rotates. This is where the name sinogram comes from: the curves resemble sine waves.

Once you recognize these patterns, you will never look at projection data the same way again.

Each row contains a projection from one angle. A point source follows a sinusoidal path as the angle changes.

Step 3: Can we simply "redistribute" the projections back?

A surprisingly intuitive idea is to take every projection and spread (or back-project) its measured counts across the image.

Repeat this for every angle, and eventually an image starts to appear.

It works…

…sort of.

The reconstructed object becomes blurry because every measurement is spread over an entire line rather than placed exactly where it originated. Even with many projections, simple back-projection produces streaking and a $1/r$ blur.

Each new projection adds information, but it also spreads counts across the image.

Step 4: Filtering sharpens the image

The solution is elegant.

Before back-projecting, we first filter the projection data.

This compensates for the blurring introduced by simple back-projection, producing what is known as filtered back projection (FBP).

Different filters make different trade-offs:

sharper images;
less image noise; or
a smoother appearance.

Finding the right balance is one of the classic challenges in medical image reconstruction.

Filtering reduces the characteristic haze of simple back-projection and makes the source easier to localize.

Seeing it makes all the difference

When I first started learning and, later on, teaching image reconstruction, I realized that static figures only go so far.

Some of the best animations I have ever used were created by my colleague Adam Kesner, whose visualizations beautifully show how projections, sinograms, and back-projection work. Those animations have helped generations of students develop an intuitive understanding of tomographic imaging. You can find them on his Website3D Image Reconstruction Explained with Animated GIFsAdam KesnerMedical physics education resourceVisit the website .

They also inspired me to build something interactive.

Instead of simply watching the reconstruction happen, I wanted people to be able to play with and control it themselves—changing the number of projections, seeing the sinogram update in real time, and watching the image emerge step by step.

That became the inspiration for the TheranosticsBytes SPECT Reconstruction Applet.

👉 Interactive appletSPECT Reconstruction AppletTheranosticsBytesExplore projections, sinograms, and image reconstructionOpen the applet

I hope it gives you the same "eureka!" moment that those original animations gave me.

Final thoughts

Every SPECT image begins life as a collection of two-dimensional measurements.

Image reconstruction is the mathematical process that transforms those measurements into a three-dimensional representation of where the radiopharmaceutical is inside the body.

Once you understand projections, sinograms, and back-projection, the reconstruction process no longer feels like a black box and it becomes a fascinating example of physics, mathematics, and medicine working together.

This article is for education and discussion. It is not a substitute for patient-specific medical advice or local clinical protocols.