Review of free software tools for image analysis of fluorescence cell micrographs

By V. Wiesmann, D. Franz, Christian Held, C. Münzenmayer, Ralf Palmisano, Thomas Wittenberg. 2014

103 citations recorded by the source corpus.

An increasing number of free software tools have been made available for the evaluation of fluorescence cell micrographs. The main users are biologists and related life scientists with no or little knowledge of image processing. In this review, we give an overview of available tools and guidelines about which tools the users should use to segment fluorescence micrographs. We selected 15 free tools and divided them into stand‐alone, Matlab‐based, ImageJ‐based, free demo versions of commercial tools and data sharing tools. The review consists of two parts: First, we developed a criteria catalogue and rated the tools regarding structural requirements, functionality (flexibility, segmentation and image processing filters) and usability (documentation, data management, usability and visualization). Second, we performed an image processing case study with four representative fluorescence micrograph segmentation tasks with figure‐ground and cell separation. The tools display a wide range of functionality and usability. In the image processing case study, we were able to perform figure‐ground separation in all micrographs using mainly thresholding. Cell separation was not possible with most of the tools, because cell separation methods are provided only by a subset of the tools and are difficult to parametrize and to use. Most important is that the usability matches the functionality of a tool. To be usable, specialized tools with less functionality need to fulfill less usability criteria, whereas multipurpose tools need a well‐structured menu and intuitive graphical user interface.

Subfields: Biophysics, Media Technology, Molecular Biology, Medical Imaging, Computational Biology & Bioinformatics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biophysics

1. Shantanu Singh
2. Anne E Carpenter
3. Virginie Uhlmann
4. Allen Goodman
5. Juan C. Caicedo
6. Oren Z. Kraus

In Media Technology

1. Shantanu Singh
2. Virginie Uhlmann
3. Anne E Carpenter

In Molecular Biology

1. Shantanu Singh
2. Anne E Carpenter
3. Allen Goodman
4. Virginie Uhlmann

In Medical Imaging

1. Shantanu Singh
2. Virginie Uhlmann
3. Anne E Carpenter

In Computational Biology & Bioinformatics

1. Shantanu Singh
2. Anne E Carpenter

Citations in the corpus

• CellProfiler 4: improvements in speed, utility and usability (2021, methodology): “In an independent analysis of 15 free image analysis tools CellProfiler scored highly in both usability and functionality [5].”
• CP-CHARM: segmentation-free image classification made accessible (2016, background): “It has been independently rated as the most feature-filled and user-friendly software in its class [17].”