ITCN: Image-based Tool for Counting Nuclei

ITCN: Image-based Tool for Counting Nuclei

Author:
Thomas Kuo <thekuo[at]ece.ucsb.edu>
Jiyun Byun <jiyun[at]ece.ucsb.edu>
ITCN is based on work at the Center for Bio-image Informatics at UC Santa Barbara

Requires: ImageJ 1.34s or later

Source: Contained in ITCN_.jar, which can be opened using a ZIP utility

Installation: Download ITCN_.jar to the plugins folder or subfolder, restart ImageJ,
and there will be a new Plugins/Filters/ITCN commands.

Description:
ITCN is an ImageJ plugin for automatically counting the number cells within an image. The inputs are: (1) an estimation of the diameter of a cell, (2) an estimation of the minimum distance between cells, and (3) either a region of interest (ROI) selected with ImageJ's selection tools or a black and white mask image that is white in regions that are to be counted.

Full instructions are available at www.bioimage.ucsb.edu/itcn.html.

Future Releases:

Use of magnification information to initially estimate width and minimum distance.

Advanced options including Threshold level and dot/line colors

Options for generating a mask.

Automatic determination of cell width.

Author:	Thomas Kuo <thekuo[at]ece.ucsb.edu> Jiyun Byun <jiyun[at]ece.ucsb.edu> ITCN is based on work at the Center for Bio-image Informatics at UC Santa Barbara
Requires:	ImageJ 1.34s or later
Source:	Contained in ITCN_.jar, which can be opened using a ZIP utility
Installation:	Download ITCN_.jar to the plugins folder or subfolder, restart ImageJ, and there will be a new Plugins/Filters/ITCN commands.
Description:	ITCN is an ImageJ plugin for automatically counting the number cells within an image. The inputs are: (1) an estimation of the diameter of a cell, (2) an estimation of the minimum distance between cells, and (3) either a region of interest (ROI) selected with ImageJ's selection tools or a black and white mask image that is white in regions that are to be counted. Full instructions are available at www.bioimage.ucsb.edu/itcn.html.
Future Releases:	Use of magnification information to initially estimate width and minimum distance. Advanced options including Threshold level and dot/line colors Options for generating a mask. Automatic determination of cell width.