Drag and drop RetFM_J.jar to the “ImageJ” window or
download and install using the Plugins>Install command,
and an “RetFM J” command will appear in the Plugins menu.
RetFM-J counts, segments, and computes quantitative features of cell nuclei
in the inner retina from images of hematoxylin and eosin (H&E)-stained
Local contrast enhancement is performed using the CLAHE plugin.
Fiji includes this functionality
by default. ImageJ users, however, should install this plugin from the link above.
Since publication of the manuscript referenced above, the RetFM-J plugin
has been amended to output all data (i.e. the number of nuclei counted,
feature information for each nucleus, and area measurements for all analyzed
images) in a single spreadsheet rather than in three separate files as described
in the manuscript.
For guidance on the use of RetFM-J, detailed instruction may be found
in the manuscript referenced below.
Test images: Included are a high density test image
and a low density test image, captured at a total
magnification of 200X (1360 x 1024 px) from whole-mounted retinas stained
with H&E for preliminary test runs of RetFM-J. The image exhibiting a high density
of nuclei is from a mouse with no overt disease (C57BL/6J). The image with a low
density of nuclei is from the diseased retina of a mouse with glaucoma (DBA/2J).
Hedberg-Buenz et. al. RetFM-J, an ImageJ-based module for automated
counting and quantifying features of nuclei in retinal whole-mounts.
Exp Eye Res (2015). [PMID: 26283021].
Authors: Christopher Mei (christopher.mei at sophia.inria.fr) Anthony Joshua (Anthony.Joshua at utoronto.ca) Tony Collins (tonyc at uhnresearch.ca) History: 2003/12/15 : First version 2005/06/15: Added 16-bit version
Authors: Ignacio Arganda-Carreras (ignacio.arganda at gmail.com) Stephan Saalfeld Johannes Schindelin Source: In siox_.jar Requires: ImageJ 1.43m or later Installation: Drag and drop siox_.jar onto the
Author: Dimiter Prodanov (dimiterpp at gmail.com) History: 2013/03/22: First release Source: Blob_Labeler.java Installation: Drag and drop Blob_Labeler.class onto the “ImageJ” window. Description: The plugin labels