The page below contains more information about the tomography-inspired art works submitted to our contest. The artists have put a lot of effort in their works, so give this page a read!
CONTEST WINNER: "Ceci n’est pas un artichaut" by Davide Borghi
The aim of the composition is to show how Computed Tomography can be used to portray nature in its beauty, as a tool to look inside it in an artistic as well as diagnostic and technical way.
This image was obtained from a CT scan performed with a low-cost prototype CT system, which is described in the poster titled «Realization of a low-cost prototype CT system using common tools». The scan was performed with just 360 radiographs using a 70kV «dental» tube and a lens-coupled detector with a 0,077mm pixel pitch. The magnification was set to obtain a voxel size of 0,064mm. The reconstructed volume was then imported in an image editing software, where it was overlayed with a colorful circular pattern, animated to rotate from the start to the end of the volume, with the aim to create the spiraling stripes that are visible on the artichoke’s surfaces. The coloured CT volume was then imported in myVGL where it was rendered with «volume render» mode, and adding shadows. The obtained 3D image was then corrected for vibrance, tone, and contrast.
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"Tomography in 2024/4/20" by Thomas Lang
This work contains X-ray computed tomography scans of a turtle and Cannabis plants. From both scans, the surfaces were extracted and simulations were performed on each of the scans to get true-to-life projections. Both scans were then manually composed to obtain the overall image.
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"OWL — An Artistic Exploration of Medical Design" by Herminso Villarraga-Gómez
Experience an intriguing visual exploration of a dry powder inhaler's inner workings through this puzzling collection of X-ray and CT images. These snapshots reveal the intricate design and assembly of the inhaler's drug delivery system, showcasing its striking owl-like silhouette—an unexpected aesthetic found within a medical device. Captured using advanced imaging techniques, the CT processing utilized a materials-aware reconstruction software (MARS) to reduce artifacts from the metal inserts in plastic parts. This fusion of science and art not only highlights the inhaler's functional design but also invites viewers to appreciate the hidden beauty inherent in everyday medical devices.
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"Noodles in the beamline" by Wannes Goethals
No, we didn't put noodles in the flow cell. To quickly find the sample outline during a great beamtime at Tomcat, I used ImageJ to perform a maximal intensity projection over every 100'th reconstructed slice. The lines with higher intensity are actually the boundaries of the rock matrix, where the edges are enhanced by the phase contrast.
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"Sanctogram" by Joaquim Sanctorum
A sinogram of a mysterious object. You can find out yourself what the object is by reconstructing it (360 degree rotation, 2D parallel beam geometry). Hint: reconstruct the RGB channels separately and merge them again in one RGB picture.
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"Unveiling Djed-Hor" by Henry Weber
The image shows various stages of the virtual exposure of the mummy of Djed-Hor, son of Peti and Ta-men, from the Middle Egyptian city of Achmim.
The mummy, which dates from the Ptolemaic period (around the 3rd century BC), was examined in 2022 at the Heidelberg Centre for Cultural Heritage (HCCH) using computed tomography (CT) in an attempt to gain a non-destructive view of the mummy's interior and new insights into Djed-Hor's life, medical history and cause of death (mastoiditis).
In addition to the medical CT scans, optical scans were taken of the closed and open sarcophagus, with and without the death mask (the three images on the left), in order to faithfully capture the external colouring.
The data obtained in this way formed the basis for the renderings which I created in VGSTUDIO MAX. I also used this software to perform the segmentation that allowed me to gradually reveal the mummified body of Djed-Hor.
The final compositing was done in Photoshop.
Credits:
CT scan: Dr Roman Sokiranski
Optical scan: Knut Lehmann, klib3Dscanner
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"Art forms of artifacts" by Dominik Müller
The graphic is a reinterpretation of a poster art in art nouveau style, substantially inspired by Ernst Haeckel's panels from his Art Forms in Nature and the early cyanotypes of technical drawings.
Normally, the measurement data of an object is the desired result. Disturbing artefacts, as by-products or waste, are elaborately filtered out and disappear from the data sets without a trace in order to hide them from the viewer's eyes. ‘Art forms of artefacts’ reverses this approach. The valuable measurement result of the object moves centrally into the background, the artefacts filtered out in the reconstruction and post-processing are not only shown, they are a prominent main component of the graphic. When it is not a question of a measurement result, these artefacts, which are normally never seen in isolation, can unfold their beauty from their symmetry.
The individual panels of the graphic are all taken from one horizontal sectional image of a high-resolution CT measurement of a fragment of the iron-nickel meteoroid ‘Mont Dieu’, slice no. 242. Instead of simply filtering out the inevitable measurement artefacts, they have been separated here and placed individually next to the measurement image. The new result is a graphical table of the artefacts. The Mont Dieu meteorite is one of the largest meteoroids ever found in Europe. It was discovered in France in 1994 and consists mainly of an iron-nickel alloy with inclusions of sulphites and silicates. The measurements were carried out using the in-house ntCT Nano-CT. This is a projection-based CT with a resolution of up to 150 nm.
The data reconstruction was carried out using a filtered back projection in the in-house Reco software, which is specifically adapted to the nano-CT. In addition to the reconstruction with all commonly used enhancement filters, the data set was also reconstructed without ring filter and motion correction in order to form difference images. The ring filter was then run again step by step in the PyXit software. Next, the resulting images were separated into three color areas using a threshold value.
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