title: Biologically inspired EM image alignment and neural reconstruction.
abstract: BACKGROUND
  Three-dimensional reconstruction of consecutive serial-section transmission electron microscopy (ssTEM) images of neural tissue currently requires many hours of manual tracing and annotation. Several computational techniques have already been applied to ssTEM images to facilitate 3D reconstruction and ease this burden.
  
  
  RESULTS
  Here, we present an alternative computational approach for ssTEM image analysis. We have used biologically inspired receptive fields as a basis for a ridge detection algorithm to identify cell membranes, synaptic contacts and mitochondria. Detected line segments are used to improve alignment between consecutive images and we have joined small segments of membrane into cell surfaces using a dynamic programming algorithm similar to the Needleman-Wunsch and Smith-Waterman DNA sequence alignment procedures. A shortest path-based approach has been used to close edges and achieve image segmentation. Partial reconstructions were automatically generated and used as a basis for semi-automatic reconstruction of neural tissue. The accuracy of partial reconstructions was evaluated and 96% of membrane could be identified at the cost of 13% false positive detections.
  
  
  BACKGROUND
  An open-source reference implementation is available in the Supplementary information.
  
  
  BACKGROUND
  seymour.kb@ed.ac.uk; douglas.armstrong@ed.ac.uk
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: School of Informatics, The University of Edinburgh, Edinburgh, UK. seymour.kb@ed.ac.uk
authors: Seymour
authors: S
authors: Knowles-Barley
authors: Nancy J
authors: NJ
authors: Butcher
authors: Ian A
authors: IA
authors: Meinertzhagen
authors: J Douglas
authors: JD
authors: Armstrong
mesh_terms: D000465:Algorithms; D000818:Animals; D002462:Cell Membrane / Q000648:ultrastructure; D004330:Drosophila / Q000648:ultrastructure; D021621:Imaging, Three-Dimensional; D046529:Microscopy, Electron, Transmission / Q000379:methods*; D009474:Neurons / Q000648:ultrastructure*