Published February 12, 2024 | Version 1.0
Dataset Open

Fraunhofer EZRT XXL-CT Instance Segmentation Me163

  • 1. Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS
  • 2. Deutsches Museum
  • 3. Friedrich-Alexander-Universität Erlangen-Nürnberg

Description

The ’Me 163’ was a Second World War fighter airplane and a result of the German air force secret developments. One of these airplanes is currently owned and displayed in the historic aircraft exhibition of the ’Deutsches Museum’ in Munich, Germany. To gain insights with respect to its history, design and state of preservation, a complete CT scan was obtained using an industrial XXL-computer tomography scanner.

Using the CT data from the Me 163, all its details can visually be examined at various levels, ranging from the complete hull down to single sprockets and rivets. However, while a trained human observer can identify and interpret the volumetric data with all its parts and connections, a virtual dissection of the airplane and all its different parts would be quite desirable. Nevertheless, this means, that an instance segmentation of all components and objects of interest into disjoint entities from the CT data is necessary.

As of currently, no adequate computer-assisted tools for automated or semi-automated segmentation
of such XXL-airplane data are available, in a first step, an interactive data annotation and object labeling process has been established. So far, seven sub-volumes from the Me 163 airplane have been annotated and labeled, whose results can potentially be used for various new applications in the field of digital heritage, non-destructive testing, or machine-learning. These annotated and labeled data sets are available here.

Files

trainingVolume-V1-(3072,4608,0).zip

Files (1.0 GB)

Name Size Download all
md5:9a3e597c9a3348893d7d980ab07a449a
136.4 MB Preview Download
md5:ba8d06321976f3171367a0412c783b23
135.7 MB Preview Download
md5:95ada824101e874ed78a9ae7a13fe4be
135.5 MB Preview Download
md5:c0231f1616ed4f54532bd0d67b8e3e83
146.2 MB Preview Download
md5:94f5bcf9dd36e85141d2a64a5a3b7816
164.8 MB Preview Download
md5:bdd5c46c77847b33b9daa5146dff7668
160.6 MB Preview Download
md5:2d503c2f27b7437ea7dcf651746f0ffd
133.3 MB Preview Download

Additional details

Related works

Is described by
Preprint: 10.48550/arXiv.2212.08639 (DOI)
Data paper: 10.1038/s41597-024-03347-4 (DOI)