ITCN 1.6 – ImageJ Plugin for Image-based Tool for Counting Nuclei

ITCN 1.6

:: DESCRIPTION

ITCN (Image-based Tool for Counting Nuclei) is an ImageJ plugin for 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
  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

::DEVELOPER

The Center for Bio-Image Informatics

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

ITCN

:: MORE INFORMATION

Download itcn_.jar to the plugins folder of ImageJ and restart ImageJ.

BQBisqueJ 0.1 – ImageJ plugin for Bisque DataBase System

BQBisqueJ 0.1

:: DESCRIPTION

BQBisqueJ is an ImageJ plugin that allows direct access to the Bisque DataBase system.

::DEVELOPER

The Center for Bio-Image Informatics

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

BQBisqueJ ; Source Code

:: MORE INFORMATION

BQBisqueJ requires adding a Bisque JAR file to ImageJ. In ImageJ 1.31 or later, this is done by copying the Bisque JAR file into the plugins folder or an immediate subfolder of the plugins folder, then restarting ImageJ.

bioView 1.1.18 – Visualize EM, Confocal, etc. Biology Imagery

bioView 1.1.18

:: DESCRIPTION

bioView is an open source and cross-platform application intended for biologists to visualize EM, Confocal, etc. imagery. It also provides access from the remote controller that simplifies usage of the very large screens e.g. 8000×4800 pixels composed by many monitorsa and is used on iWall.

bioView can receive external control clients, it uses TCP/IP connection and listens on the port specified in wv.ini file, the default is 9229. Upon connection client will receive preview of currently open image and enable controls.

::DEVELOPER

The Center for Bio-Image Informatics

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX

:: DOWNLOAD

bioView

:: MORE INFORMATION

Citation:

Kristian Kvilekval, Dmitry Fedorov, Boguslaw Obara, Ambuj Singh and B.S. Manjunath,
Bisque: A Platform for Bioimage Analysis and Management
Bioinformatics, vol. 26, no. 4, pp. 544-552, Feb. 2010.

Digital Notebook 1.2.28 – Image Management & Annotation

Digital Notebook 1.2.28

:: DESCRIPTION

Digital Notebook is designed to simplify the image annotation process. It allows researchers to create meta-data required by the bio-image database. It can also update, print and upload existing information.

Digital Notebook is a digital notebook for biologists to manage image collections and related metadata both on their local machines and for integrating with the BISQUE database. The Digital Notebook eases the management and creation of metadata descriptions of large volumes of images by using domain knowledge to relieve the biologist of repetetive tasks. The metadata entry system is fully customizable to the specific need of an image set through an editable XML config file that stores information about what metadata fields are necessary for a certain class of images as well as default and common values for those fields. The Digital Notebook also has a built in file browser for easily navigating sets of images kept in separate folders. It can read JPEG, TIFF, and PNG formatted image files and stores the metadata in a companion XML file next to the image.

::DEVELOPER

The Center for Bio-Image Informatics

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Bisque

:: DOWNLOAD

Digital Notebook

:: MORE INFORMATION

Citation:

Kristian Kvilekval, Dmitry Fedorov, Boguslaw Obara, Ambuj Singh and B.S. Manjunath,
Bisque: A Platform for Bioimage Analysis and Management
Bioinformatics, vol. 26, no. 4, pp. 544-552, Feb. 2010.

Segtrack – C++ & MatLab Library for Image Tracking & Segmentation

Segtrack

:: DESCRIPTION

Segtrack is a library of MATLAB functions useful for prepocessing, segmenting, tracking, postprocessing, and other tasks used for treating biological image data. See the html main_index file included in the dowload package for more details.

::DEVELOPER

Scientific Inference Systems Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • MATLAB

:: DOWNLOAD

Segtrack

:: MORE INFORMATION

This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version.

contact:
T.Bacarian
tbacaria@uci.edu

Sassign 2 – C++ & MatLab Library for Image Target Tracking

Sassign 2

:: DESCRIPTION

SASSIGN is a tracking software based on softassign matching algorithm. sassign is C++ and MATLAB package for tracking larger numbers of closely positioned cells (landmarks) with similar geometrical characteristics through timeseries of frames where some cells may divide into two daughter cells. Each frame may contains repositioned cells from the previous frame with some of them divided into two parts, and/or a few number of outliers e.g. cells appeared/disappeared from the boundaries of the frame or miscounted due to preprocessing errors. The C++ processing module is based on an advanced version of the softassign algorithm where simulated annealing is used to minimize a global target function over all possible parent-parent or parent-daughters associations of cells. The Matlab part of the package consists of wrapper routines for running the code and building hierarchical tree of the cells evolution

::DEVELOPER

Scientific Inference Systems Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • MATLAB

:: DOWNLOAD

Sassign

:: MORE INFORMATION

Tracking Cell Signals in Fluorescent Images; Gor et. al. (CVPR2005)

Costanza 1.0 – ImageJ Plugin for Image Segmentation & Analyzing Stacks

Costanza 1.0

:: DESCRIPTION

Costanza (COnfocal STack ANalyZer Application) is a Image segmentation software developed for 3D confocal data. Implemented in Java as a plugin to ImageJ.

Costanza is used to segment compartments (cells) in a stack and to extract quantitative data for the extracted compartments, including intensities from a second stack.

::DEVELOPER

Michael Green, Pawel Krupinski, Pontus Melke, Patrik Sahlin, Henrik Jönsson
Computational Biology & Biological Physics, Lund University

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

Costanza ; userguide.pdf.

:: MORE INFORMATION

Source code is available upon request (henrik at thep.lu.se).

CLSM Tools 20080903 – MATLAB Library for Nuclear Segmentation & Lineage Analysis

CLSM Tools 20080903

:: DESCRIPTION

CLSM Tools is a MATLAB library for nuclear segmentation and lineage analysis.

CLSM or LSCM (Confocal laser scanning microscopy) is a technique for obtaining high-resolution optical images with depth selectivity.

::DEVELOPER

Biological Network Modeling Center

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • MATLAB

:: DOWNLOAD

CLSM Tools

:: MORE INFORMATION

CLSM Tools is available from the BNMC for the campus community.

MAGIC Tool 2.1 – MicroArray Genome Imaging & Clustering Tool

MAGIC Tool 2.1

:: DESCRIPTION

MAGIC Tool is an integrated microarray data analysis software.

The purpose of MAGIC Tool is to allow the user to begin with DNA microarray tiff files and end with biologically meaningful information. Comparative hybridization data (glass chips) and Affymetrix data are compatible with MAGIC Tool. You can start with tiff files or expression files.

MAGIC Tool allows the user to change parameters for clustering, data quantification etc.

::DEVELOPER

Laurie Heyer

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Mac/ Linux/ UNIX
  • Java

:: DOWNLOAD

MAGIC Tool ;  User’s Guide

:: MORE INFORMATION

Free software with open source.

Paper: MAGIC Tool: Integrated microarray data analysis (Bioinformatics, 2005)

Spotfinder v3.2.1 – Microarray Images Analysis & Gene Expression Quantification

Spotfinder v3.2.1

:: DESCRIPTION

Spotfinder is an image processing program created at The Institute for Genomic Research (J. Craig Venter Institute now) for analysis of the image files generated in microarray expression studies. Spotfinder uses a fast and reproducible algorithm to identify the spots on array and provide quantitation of expression levels.

Image analysis is a crucial step in the microarray process. TIGR Spotfinder was designed for the rapid, reproducible and computer-aided analysis of microarray images and the quantification of gene expression. TIGR Spotfinder reads paired 16-bit or 8-bit TIFF image files generated by most microarray scanners. Semi-automatic grid construction defines the areas of the slide where spots are expected. Automatic and manual grid adjustments help to ensure that each rectangular grid cell is centered on a spot. Two available segmentation methods (histogram and Otsu) define the boundaries between each spot and the surrounding local background. Spot intensities are calculated as an integral of non-saturated pixels, although other options including spot median and mean values are available. Local background subtraction for each reported value is applied by default but can be disabled. The calculated intensities, medians, and means along with each spot position on the array, spot area, background values, and quality control flags are written to a MEV file or the database. Reusable grid geometry files and automatic grid adjustment allow user to analyze large quantities of images in a consistent and efficient manner. To complement the automated methods, particularly in noisy areas of the slide, the user may manually identify or discard spots. Quality control views allow the user to assess systematic biases in the data.

::DEVELOPER

J. Craig Venter Institute

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Mac OS X on Intel chips/Mac OS X on PowerPC chips/Linux

:: DOWNLOAD

Spotfinder v3.2.1 for Win ; for Mac OS X on Intel chips ; for Mac OS X on PowerPC chips ; for Linux ; Manual ; Source Code ; Training Documents

:: MORE INFORMATION

Referencing Spotfinder

Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J. TM4: a free, open-source system for microarray data management and analysis. Biotechniques. 2003 Feb;34(2):374-8.

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