@article{SchlegelSauer2020,
  author    = {Schlegel, Jan and Sauer, Markus},
  title     = {Hochaufgel{\"o}ste Visualisierung einzelner Molek{\"u}le auf ganzen Zellen},
  series = {BIOspektrum},
  volume    = {7},
  journal   = {BIOspektrum},
  issn      = {0947-0867},
  doi       = {10.1007/s12268-020-1501-4},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232365},
  pages     = {736-738},
  year      = {2020},
  abstract  = {Biological systems are dynamic and three-dimensional but many techniques allow only static and two-dimensional observation of cells. We used three-dimensional (3D) lattice light-sheet single-molecule localization microscopy (dSTORM) to investigate the complex interactions and distribution of single molecules in the plasma membrane of whole cells. Different receptor densities of the adhesion receptor CD56 at different parts of the cell highlight the importance and need of three-dimensional observation and analysis techniques.},
  language  = {de}
}
@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}
}