A novel two-staged deep learning based workflow for analyzable metaphase detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17509-w.pdf
Reference56 articles.
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2. King RC, Stansfield WD, Mulligan PK (2006) A dictionary of genetics. Oxford University Press
3. RemaniSathyan R, Chandrasekhara Menon G, Thampi R, Duraisamy JH (2022) Traditional and deep-based techniques for end-to-end automated karyotyping: A review. Expert Syst 39(3):e12799. https://doi.org/10.1111/exsy.12799
4. Wang X, Li S, Liu H, Wood M, Chen WR, Zheng B (2008) Automated identification of analyzable metaphase chromosomes depicted on microscopic digital images. J Biomed Inform 41(2):264–271. https://doi.org/10.1016/j.jbi.2007.06.008
5. Uttamatanin R, Yuvapoositanon P, Intarapanich A, Kaewkamnerd S, Phuksaritanon R, Assawamakin A, Tongsima S (2013) MetaSel: a metaphase selection tool using a Gaussian-based classification technique. BMC Bioinformatics 14(16):1–13. https://doi.org/10.1186/1471-2105-14-S16-S13
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