3D volume segmentation and reconstruction. Supervised image classification and automated quantification of superparamagnetic iron oxide nanoparticles in histology slides for safety assessment-Reference-Cited by-同舟云学术

3D volume segmentation and reconstruction. Supervised image classification and automated quantification of superparamagnetic iron oxide nanoparticles in histology slides for safety assessment

Published:2021-11-09 Issue: Volume: Page:1-17
ISSN:1743-5390
Container-title:Nanotoxicology
language:en
Short-container-title:Nanotoxicology

Author:

Bogdanska Anna¹²^ORCID,Gobbo Oliviero L.²³^ORCID,Volkov Yuri¹²⁴,Prina-Mello Adriele¹²⁴^ORCID

Affiliation:

1. Nanomedicine and Molecular Imaging Group, Trinity Translational Medicine Institute, Trinity College Dublin, the University of Dublin, Dublin, Ireland

2. Trinity St James’s Cancer Institute, Trinity College Dublin, the University of Dublin, Dublin, Ireland

3. School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, the University of Dublin, Dublin, Ireland

4. Laboratory of Biological Characterization of Advanced Materials (LBCAM), Trinity Translational Medicine Institute, Trinity College Dublin, the University of Dublin, Dublin, Ireland

Funder

European Commission

Publisher

Informa UK Limited

Subject

Toxicology,Biomedical Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/17435390.2021.1991502

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1. Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification

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4. Macrophage labeling by SPIO as an early marker of allograft chronic rejection in a rat model of kidney transplantation

5. SegEM: Efficient Image Analysis for High-Resolution Connectomics

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