Artificial intelligence-assisted identification and quantification of osteoclasts-Reference-Cited by-同舟云学术

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Artificial intelligence-assisted identification and quantification of osteoclasts

Published:2021 Issue: Volume:8 Page:101272
ISSN:2215-0161
Container-title:MethodsX
language:en
Short-container-title:MethodsX

Author:

Emmanuel Thomas^ORCID,Brüel Annemarie^ORCID,Thomsen Jesper Skovhus^ORCID,Steiniche Torben,Brent Mikkel Bo^ORCID

Funder

Oda og Hans Svenningsens Fond

Kongelig Hofbuntmager Aage Bangs Fond

Direktor Emil C Hertz og Hustru Inger Hertz Fond

Civilingeniør Frode V Nyegaard Og Hustrus Fond

Dagmar Marshalls Fond

AP Møller Fonden

Helga and Peter Kornings Fund

Frimodt Henike Foundation

Torben og Alice Frimodts Fond

Aase og Ejnar Danielsens Fond

Publisher

Elsevier BV

Subject

Medical Laboratory Technology,Clinical Biochemistry

Reference8 articles.

1. Osteoclasts: new insights;Xu;Bone Res.,2013

2. Formation and function of the ruffled border in osteoclasts;Stenbeck;Semin. Cell Dev. Biol.,2002

3. Optimization of the tartrate-resistant acid hosphatase detection by histochemical method;Galão;Eur. J. Histochem.,2011

4. Open source software for semi-automated histomorphometry of bone resorption and formation parameters;van ’t Hof;Bone,2017

5. An optimized approach to perform bone histomorphometry;Malhan;Front. Endocrinol. (Lausanne).,2018

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1. Impact of functional electrical stimulation on nerve-damaged muscles by quantifying fat infiltration using deep learning;Scientific Reports;2024-05-28

2. A Machine Learning-Based Image Segmentation Method to Quantify In Vitro Osteoclast Culture Endpoints;Calcified Tissue International;2023-08-11

3. Contemporary Advances in Computer-Assisted Bone Histomorphometry and Identification of Bone Cells in Culture;Calcified Tissue International;2022-10-29

4. Automated Quantification of Human Osteoclasts Using Object Detection;Frontiers in Cell and Developmental Biology;2022-07-05

5. OC_Finder: Osteoclast Segmentation, Counting, and Classification Using Watershed and Deep Learning;Frontiers in Bioinformatics;2022-03-25

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