Back to Search Start Over

Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images.

Authors :
Piccinini, Filippo
Tazzari, Marcella
Tumedei, Maria Maddalena
Stellato, Mariachiara
Remondini, Daniel
Giampieri, Enrico
Martinelli, Giovanni
Castellani, Gastone
Carbonaro, Antonella
Source :
Sensors (14248220); Jan2024, Vol. 24 Issue 2, p451, 20p
Publication Year :
2024

Abstract

Most of the time, the deep analysis of a biological sample requires the acquisition of images at different time points, using different modalities and/or different stainings. This information gives morphological, functional, and physiological insights, but the acquired images must be aligned to be able to proceed with the co-localisation analysis. Practically speaking, according to Aristotle's principle, "The whole is greater than the sum of its parts", multi-modal image registration is a challenging task that involves fusing complementary signals. In the past few years, several methods for image registration have been described in the literature, but unfortunately, there is not one method that works for all applications. In addition, there is currently no user-friendly solution for aligning images that does not require any computer skills. In this work, DS4H Image Alignment (DS4H-IA), an open-source ImageJ/Fiji plugin for aligning multimodality, immunohistochemistry (IHC), and/or immunofluorescence (IF) 2D microscopy images, designed with the goal of being extremely easy to use, is described. All of the available solutions for aligning 2D microscopy images have also been revised. The DS4H-IA source code; standalone applications for MAC, Linux, and Windows; video tutorials; manual documentation; and sample datasets are publicly available. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
2
Database :
Complementary Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
175129667
Full Text :
https://doi.org/10.3390/s24020451