Two years ago I had a post here (follow-up) where I dared to compare these two programs. The reaction was unfavorable. The ImageJ ticket quoted below seems to indicate that there has been a slight shift.

Wayne [Rasband] had an idea for a command called “Analyze Image” that combines filtering, background correction, segmentation, particle analysis, etc. It would work something like the closed-source, Windows-only  Pixcavator program. As Wayne said, “It would not be an easy thing to create but it would be very popular with ImageJ users. 

I agree.

Prof. Marian Mrozek  was kind enough to inform me about the coming update of CHomP in his email that I quote below:

The power of the software comes from much newer algorithms. Some of them are described in the papers:

• M. Mrozek, P. Pilarczyk, N. Zelazna, Homology algorithm based on acyclic subspace, Computers and Mathematics with Applications, 55 (2008), 2395 –2412.
• M. Mrozek, B. Batko, Coreduction homology algorithm, Discrete and Computational Geometry, 41 (2009), 96-118.
• M. Mrozek, Cech Type Approach to Computing Homology of Maps
  Discrete and Computational Geometry, accepted
• and a few more which are just in preparation.

We just finish[ed] writing a new, much stronger version of the software which will accept not only cubical complexes but also simplicial complexes and general CW complexes and will produce broader output, in particular homology generators, homology maps and persistence intervals for filtered complexes.

The new version of our software at first will be available from the webpage
of our CAPD group at Jagiellonian University, Krakow, Poland:
http://capd.ii.uj.edu.pl/.

Take a look also at our Homology Software page.

These are the new features in version 5.0.

• Your choice of settings in the Output tab (the position of the sliders) is preserved when you load a new image to analyze.
• Your choice of color channels in the Analysis tab is preserved when you load a new image to analyze. With these two the user can apply the same settings to a sequence of images if they are similar in nature. So, we get as close as possible to bulk processing without actually creating this complex feature.
• Luminosity is a new color channel that you can choose. It is computed as a combination of the red, green, and blue values: 0.299*R + 0.587*G + 0.114*B. There are four channels now.
• “Display channel” is a new option in the Analysis tab (just like the one in the Output tab). If you have chosen to shrink the image, the shrunken version is shown. This way you can preview all channels and decide which is the best – before committing to time consuming analysis.
• The “Help” menu provides now the links to the help pages of this wiki. The user’s guide and the license are still provided with the program; they are to be found in the “Pixcavator” folder on your hard disk.
• The actual processing time is shown when it’s done, and a beep is produced – but only if processing has taken more than 5 seconds.
• Up to 2000 contours are now shown on the image and their statistics is also displayed. When there are more than 2000 contours, neither is shown.
• A few bugs have been fixed, some remain.

Download here.

A new research paper that uses Pixcavator:

Adsorption Dynamics of CO on Silica Supported Gold Clusters: Cluster Size Effects in Molecular Beam Scattering Experiments by E. Kadossov, U. Burghaus (Department of Chemistry, Biochemistry, and Molecular Biology, North Dakota State University), link, published in Catalysis Letters.

From the paper:

“We report on particle size effects in the adsorption dynamics (gas-surface energy transfer) of CO, studied by molecular beam scattering… the effect of supported nano-size gold metal clusters on gas-surface energy transfer processes (adsorption dynamics)… For the statistical analysis, commercial imaging analysis software (Pixcavator IA 4.2) was used.”

There are nine, to the best of my knowledge, research papers that used Pixcavator and gave credit.

This fall I have been teaching Topology I (Topology II next spring). I decided to emphasize algebraic topology and in fact started with it rather than point set topology which alone can take two semesters.

Outline
This is an introductory, two semester course on algebraic topology and its applications. It is intended for advanced undergraduate and beginning graduate students.

Part 1. Introduction to algebraic topology
Starts with topological issues in digital image analysis, informal introduction of homology

Part 2. Homology theory
Cubical complexes, their homology, and maps

Part 3. Overview of point-set topology
Minimized to the extreme (still could have cut even more)

Part 4. Homology groups
A more formal, group theory based, exposition

Part 5. Homology and uncertainty
Applications in computer vision, image analysis and data analysis

Part 6. Beyond homology
The fundamental group and cohomology

Also, I ran across this white paper from Hewlett-Packard: Algebraic topology for computer vision. Good review and an honest attempt to convince the practitioners to that this is something that they might need to know (good luck with that!).

From simplicity comes complexity. And beauty!

A new paper that uses Pixcavator:

Down-regulation of CXCR4 and CD62L in Chronic Lymphocytic Leukemia Cells Is Triggered by B-Cell Receptor Ligation and Associated with Progressive Disease [1] by Amalia Vlad, Pierre-Antoine Deglesne, Re´mi Letestu, Ste´phane Saint-Georges, Nathalie Chevallier, Fanny Baran-Marszak, Nadine Varin-Blank, Florence Ajchenbaum-Cymbalista, and Dominique Ledoux (Cancer Research 69, 6387, August 15, 2009).

From the paper:

“Progressive cases of B-cell chronic lymphocytic leukemia (CLL) are frequently associated with lymphadenopathy, highlighting a critical role for signals emanating from the tumor environment in the accumulation of malignant B cells.”

“BCR-stimulated and unstimulated fluorescent cells were mixed in RPMI 1640/10% FCS and added together onto the endothelial cell layer. After incubation for 2 h at 37jC, the nonadherent CLL cells were washed off. Remaining adherent cells were fixed, and 10 fields from duplicate chamber slides (average of 500 cells/field) were photographed under fluorescent microscope. Red and green fluorescence were separately quantified using the Pixcavator IA 3.3 software (Intelligence Perception Co.).”

Take a look at other papers that use Pixcavator.

TechCrunch deadpools Riya. Certainly, no surprise to me. Their technology was never been impressive (posts are here). Like.com remains but does not seem to be going anywhere…

At least TechCrunch announced this death after promoting Riya for 3 years. Others have died or will die more quietly.

A paper that uses Pixcavator has been published:     

CELL METAL SEGREGATION AND ULTRAMICROSCOPY TECHNIQUES: TOWARDS MAMMALIAN LIVER PATHOLOGIES CHARACTERIZATION [1] by Marziale Milani, Claudio Savoia, Claudia Brundu, Francesco Tatti, Grazia Santisi.

From the paper:

“Iron, Copper and Zinc are essential metals in physiological cell metabolism… Our work based on ultramicroscopy techniques focuses on some aspects of metal transport in terms

of segregation, storage and distribution among the different cell compartments. An important goal is the understanding of granule building and disruption.”

“To analyze data obtained from map analysis the Pixcavator software 1.2.1 (Intelligent Perception) has been employed.”    

Spatial distribution of Cu, Zn, P and S spots in two S-cells. The graph was performed using the coordinates x, y obtained via Pixcavator.

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