
Imaging · Built from a recipe
Walnut CT
D4 on the major comb. Its drum rings at 309.1 Hz.
This is a real walnut, scanned with X-ray CT at CWI in Amsterdam: more than a thousand X-ray pictures taken from all around it, worked back into a volume of how dense the walnut is at every point.
- Shelf
- Imaging
- Kind
- Built from a recipe
- Made from
- Drag up or down on the walnut to cut into it.
- Sound
- Yes
- Licenses
- CC BY 4.0
Its note
Splashery stretches a drumhead over this Splash's outline, twelve inches across, and finds the ways it can ring. Its lowest is 309.1 Hz, 89 cents sharp of D4, the nearest tine on the comb. The next fifteen are its overtones, and each one draws its own figure: sand gathers on the lines that stay still.

- 1309 Hz
- 2466 Hz
- 3513 Hz
- 4627 Hz
- 5655 Hz
- 6728 Hz
- 7791 Hz
- 8800 Hz
- 9865 Hz
- 10939 Hz
- 11955 Hz
- 12957 Hz
- 131009 Hz
- 141069 Hz
- 151110 Hz
- 161118 Hz
How to play
Drag up or down on the walnut to cut into it. Tap to see only its shell.
Its controls
| Control | Kind | Range | Start |
|---|---|---|---|
| Shell only, or the whole walnut | Tap | ||
| Shell only | Switch | Off | |
| Cut | List | 3 choices | Front to back |
| Colors | List | 4 choices | CT gray |
About it
This is a real walnut, scanned with X-ray CT at CWI in Amsterdam: more than a thousand X-ray pictures taken from all around it, worked back into a volume of how dense the walnut is at every point. Each splat here is one small block of that volume, 0.3 mm across, bright where the walnut is dense.
Drag up or down to cut into it and see the woody shell, the kernel's folded lobes and the air between them. Choose the cut's direction and the colors (CT gray, warm, night vision or infrared) in the Splash tab. Tap to show only the densest parts: the kernel melts away and the shell stays. The scan is Walnut 1 of a dataset by Der Sarkissian, Lucka, van Eijnatten, Colacicco, Coban and Batenburg (CC BY 4.0).
Sources and credits
| Work | By | License |
|---|---|---|
| Cone-Beam X-Ray CT Data Collection Designed for Machine Learning: Samples 1-8 (Walnut 1) | Henri Der Sarkissian, Felix Lucka, Maureen van Eijnatten, Giulia Colacicco, Sophia Bethany Coban, K. Joost Batenburg (CWI) | CC BY 4.0 |



