@phdthesis{Schmid2010,
  author    = {Schmid, Benjamin},
  title     = {Computational tools for the segmentation and registration of confocal brain images of Drosophila melanogaster},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-51490},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2010},
  abstract  = {Neuroanatomical data in fly brain research are mostly available as spatial gene expression patterns of genetically distinct fly strains. The Drosophila standard brain, which was developed in the past to provide a reference coordinate system, can be used to integrate these data. Working with the standard brain requires advanced image processing methods, including visualisation, segmentation and registration. The previously published VIB Protocol addressed the problem of image registration. Unfortunately, its usage was severely limited by the necessity of manually labelling a predefined set of neuropils in the brain images at hand. In this work I present novel tools to facilitate the work with the Drosophila standard brain. These tools are integrated in a well-known open-source image processing framework which can potentially serve as a common platform for image analysis in the neuroanatomical research community: ImageJ. In particular, a hardware-accelerated 3D visualisation framework was developed for ImageJ which extends its limited 3D visualisation capabilities. It is used for the development of a novel semi-automatic segmentation method, which implements automatic surface growing based on user-provided seed points. Template surfaces, incorporated with a modified variant of an active surface model, complement the segmentation. An automatic nonrigid warping algorithm is applied, based on point correspondences established through the extracted surfaces. Finally, I show how the individual steps can be fully automated, and demonstrate its application for the successful registration of fly brain images. The new tools are freely available as ImageJ plugins. I compare the results obtained by the introduced methods with the output of the VIB Protocol and conclude that our methods reduce the required effort five to ten fold. Furthermore, reproducibility and accuracy are enhanced using the proposed tools.},
  subject      = {Taufliege},
  language  = {en}
}
@article{SchmidSchindelinCardonaetal.2010,
  author    = {Schmid, Benjamin and Schindelin, Johannes and Cardona, Albert and Longair, Martin and Heisenberg, Martin},
  title     = {A high-level 3D visualization API for Java and ImageJ},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-67851},
  year      = {2010},
  abstract  = {Background: Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set. Results: Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts. Conclusions: Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.},
  subject      = {Visualisierung},
  language  = {en}
}