This documentation provides instructions on how to use qualifier phase datasets for DIADEM contestants. Once you have registered your group, dataset download information will be sent to you via E-mail.
There are 5 datasets, all of which have to be reconstructed for the qualifier phase. The 5 datasets are:
2. Hippocampal CA3 Interneuron
4. Neuromuscular Projection Fibers
5. Olfactory Projection Fibers
General Download Instructions:
(Dataset - specific instructions can be found in
the readme files within each dataset description)
1. Download RAR files.
2. Extract RAR files using software of choice. As an example,
PeaZip (http://peazip.sourceforge.net/)
is free and can be downloaded for Windows and Linux
platforms.
3. Each RAR file contains 1 folder with 1 or 2 subfolders:
'Image Stacks' and/or 'Manual Reconstructions.
4. 'Image Stacks' folder will contain 2 subfolders: 'Training
Image Stacks' and 'Qualifier Image Stacks', except for datasets
where the same image stack(s) are used for both training and
qualifier data (e.g. neuromuscular and neocortical
datasets).
5. Depending on the dataset, the Training and Qualifier Image
Stacks folders will contain 1 or more subfolders each containing
an image stack.
6. All images are in TIFF format.
7. The 'Manual Reconstructions' folder contains example manually
traced reconstructions to use as templates for the training phase
of the corresponding dataset.
8. All manual reconstructions are in non-proprietary SWC format
(see FAQ for explanation of SWC format).
9. Freely available ImageJ (
http://rsbweb.nih.gov/ij/)
or Neuromantic (
http://www.rdg.ac.uk/neuromantic/)
software can be downloaded to open image stacks. Neuromantic can
also load SWC files to overlay on corresponding image stacks.
Training reconstructions will load in correct XYZ alignment with
corresponding image stacks unless otherwise specified in the
dataset-specific READMEs (see neuromuscular and neocortical
dataset READMEs in particular).
10. SWC file Z values correspond to image sequence number (top
image Z = 0, second image = 1, etc) within their associated image
stacks. In contrast, X and Y values correspond to pixel
values.
11. Neuromantic automatically converts image stacks to grayscale.
ImageJ will load image stacks in color but may require changing
default computer memory restrictions (see
http://imagejdocu.tudor.lu/doku.php?id=faq:technical:how_do_i_increase_the_memory_in_imagej
for instructions). Numerous plugins have been created for ImageJ,
some of which may aid in visualization and the reconstruction
process (see
http://rsb.info.nih.gov/ij/plugins).
12. TIFF files contain no inherent information regarding the
physical size of the captured region of interest. Therefore,
ImageJ and Neuromantic both use pixel-format X and Y coordinates
for loaded image stacks and image sequence number within an image
stack for Z coordinates (top image Z = 0, next image Z = 1, and
so on).
13. Below each dataset-specific README 'Experimental Procedures'
section, the Z distance between images when converted to pixels
is shown. This information can be used by contestants to compare
physical Z distance relative to X and Y values. Like the provided
manual reconstructions, final automated reconstruction X and Y
values should be in pixels and Z values should be in image
sequence number format.
14. The training material, including SWC files and corresponding
image stacks, is provided for contestants to compare automation
attempts against in order to aid development of accurate entries.
15. These SWC files have been traced manually by the given data
provider and serve as the standard for comparing contestants'
automatic reconstructions.
16. As subjectivity is an inherent aspect of neuronal
reconstruction, subjective reconstruction decisions may be
present in these manual traces. These traces serve as gold
standards not because they are known to be perfect but because
they reach the limits of subjective accuracy.
17. Each SWC within a dataset represents one tree. All trees
within a dataset are grouped together to create one score per
dataset.
18. Final entries will be scored only on specified neuronal trees
for which no manual reconstructions were provided (See the
"Manual Reconstruction Starting Coordinates" section in
each dataset-specific README for the specific image stacks and
structures). These structures have also been manually traced by
data providers, but the manual reconstructions are not provided
to contestants so that they can be used to score contestant
entries.
19. Finished automated traces should have the same name as is
found in the 'Manual Reconstruction Coordinates' section in each
dataset-specific README. Uploaded traces should also be placed in
as many dataset subfolders as required to ensure that dataset
files will not get mixed up. For example, an automated trace
using the starting coordinates provided for 'NC_13' should be
named 'NC_13.swc' and can be placed in a folder named
'Neocortical Layer 6 Axons'. '01' from 'Section 02' of the
Hippocampal CA3 Interneuron dataset should be '01.swc' and can be
placed in a subfolder named 'Section 02', which in turn is placed
in the folder 'Hippocampal CA3 Interneuron'.
20. All uploaded material should be contained in a parent folder
that uniquely identifies the contestant. Please be descriptive
enough with the parent folder name to ensure that contestants
will not be mixed up.
21. All registered contestants will be informed of the specific
steps to upload their results via email to the team leader
several weeks prior to the close of the contest.
22. Contact information is provided below for any questions not answered in the provided READMEs or on the DIADEM website FAQ.