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Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images
by
Tazzari, Marcella
, Remondini, Daniel
, Martinelli, Giovanni
, Castellani, Gastone
, Giampieri, Enrico
, Piccinini, Filippo
, Carbonaro, Antonella
, Tumedei, Maria Maddalena
, Stellato, Mariachiara
in
Cancer
/ correlative microscopy
/ Data Science
/ Datasets
/ Documentation
/ Fluorescent Antibody Technique
/ histology/histopathology
/ image registration
/ Immunohistochemistry
/ immunohistochemistry/immunofluorescence techniques
/ Microscope and microscopy
/ Microscopy
/ Microscopy, Fluorescence
/ Morphology
/ multimodal micrographs
/ Oncology
/ Open source software
/ Registration
/ User interface
2024
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Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images
by
Tazzari, Marcella
, Remondini, Daniel
, Martinelli, Giovanni
, Castellani, Gastone
, Giampieri, Enrico
, Piccinini, Filippo
, Carbonaro, Antonella
, Tumedei, Maria Maddalena
, Stellato, Mariachiara
in
Cancer
/ correlative microscopy
/ Data Science
/ Datasets
/ Documentation
/ Fluorescent Antibody Technique
/ histology/histopathology
/ image registration
/ Immunohistochemistry
/ immunohistochemistry/immunofluorescence techniques
/ Microscope and microscopy
/ Microscopy
/ Microscopy, Fluorescence
/ Morphology
/ multimodal micrographs
/ Oncology
/ Open source software
/ Registration
/ User interface
2024
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Do you wish to request the book?
Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images
by
Tazzari, Marcella
, Remondini, Daniel
, Martinelli, Giovanni
, Castellani, Gastone
, Giampieri, Enrico
, Piccinini, Filippo
, Carbonaro, Antonella
, Tumedei, Maria Maddalena
, Stellato, Mariachiara
in
Cancer
/ correlative microscopy
/ Data Science
/ Datasets
/ Documentation
/ Fluorescent Antibody Technique
/ histology/histopathology
/ image registration
/ Immunohistochemistry
/ immunohistochemistry/immunofluorescence techniques
/ Microscope and microscopy
/ Microscopy
/ Microscopy, Fluorescence
/ Morphology
/ multimodal micrographs
/ Oncology
/ Open source software
/ Registration
/ User interface
2024
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Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images
Journal Article
Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images
2024
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Overview
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.
Publisher
MDPI AG,MDPI
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