Stitches together any mode of serial section image data:

• TEM
• Block-face SEM
• Fluorescence Array Tomography

Fast and scalable:

• Runs on linux cluster using Sun Grid Engine API
• Align 2 to billions of images
• Approx. linear time/volume & mem/volume scaling
• Two million 4MB images align in about 8 man-hours

Handled pathologies:

• Missing tiles or whole sections
• Fragmented / small / irregular sections
• Arbitrarily rotated/translated sections
• Burns, scars, foreign matter
• Exposure inhomogeneity

Input:

• 8 or 16 bit TIF, PNG, MRC
• Simple meta-data as text or TrakEM2 XML

Output:

• Basically 1 affine or homographic transform per image tile
• Flexible output as text tables or TrakEM2 XML files

• One linear transform / tile; not an elastic aligner
• Unfinished handling of geometry-altering folds and tears
• All images in a data set must be of same fixed dimensions

• Linux cluster with (Sun / Oracle / Univa) Grid Engine.
• Fiji + TrakEM2: invaluable image and stack tools.

• Project folder 00_DOC details installation and methods
• Alignment_Tutorial walks you through a real-world example

Developed over several years at HHMI/Janelia Research Campus, originally by Louis Scheffer, and subsequently refined into current form by Bill Karsh. See reference "Automated Alignment of Imperfect EM Images for Neural Reconstruction".