TITLE: An annotated instance segmentation XXL-CT dataset from a historic airplane 

ABSTRACT: 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 512 x 512 x 512 voxel 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.
  This work describes the data acquisition process of the airplane using an
industrial XXL-CT scanner, outlines the interactive segmentation and labeling
scheme to annotate sub-volumes of the airplane's CT data, describes and
discusses various challenges with respect to interpreting and handling the
annotated and labeled data.
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 512 x 512 x 512 voxel 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.
  This work describes the data acquisition process of the airplane using an
industrial XXL-CT scanner, outlines the interactive segmentation and labeling
scheme to annotate sub-volumes of the airplane's CT data, describes and
discusses various challenges with respect to interpreting and handling the
annotated and labeled data.
An annotated instance segmentation XXL-CT dataset from a historic airplane
http://arxiv.org/abs/2212.08639v1