Applying Deep Learning to Melanocyte Counting on Fluorescent TRP1 Labelled Images of In Vitro Skin Model

Applying Deep Learning to Melanocyte Counting on Fluorescent TRP1 Labelled Images of In Vitro Skin Model

Cell counting is an important step in many biological experiments. It can be challenging, due to the large variability in contrast and shape of the cells, especially when their density is so high that the cells are closely packed together. Automation is needed to increase the speed and quality of th...

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Bibliographic Details
Main Authors: Tristan Lazard, Samy Blusseau, Santiago Velasco-Forero, Étienne Decencière, Virginie Flouret, Catherine Cohen, Thérèse Baldeweck
Format: Article
Language:English
Published: Slovenian Society for Stereology and Quantitative Image Analysis 2022-11-01
Series:Image Analysis and Stereology
Subjects:
cell counting
convolutional neural networks (cnn)
deep learning
fluorescence microscopy
histology
immunohistochemistry (ihc)
reconstructed skin
Online Access:https://www.ias-iss.org/ojs/IAS/article/view/2640

Internet

https://www.ias-iss.org/ojs/IAS/article/view/2640

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