Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans-Reference-Cited by-同舟云学术

Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans

Published:2020-06-21 Issue:9 Volume:58 Page:1947-1964
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med Biol Eng Comput

Author:

da Silva Giovanni L. F.^ORCID,Diniz Petterson S.,Ferreira Jonnison L.,França João V. F.,Silva Aristófanes C.,de Paiva Anselmo C.,de Cavalcanti Elton A. A.

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11517-020-02199-5.pdf

Reference57 articles.

1. American cancer society: key statistics for prostate cancer (2018). https://www.cancer.org/cancer/prostate-cancer/about/key-statistics.html. Accessed: 2018-04-15

2. Instituto nacional do câncer, tipos de câncer: Próstata (2018). http://www2.inca.gov.br/wps/wcm/connect/tiposdecancer/site/home/prostata. Accessed: 2018-04-15

3. Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Süsstrunk S (2012) Slic superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274–2282

4. Al-Qunaieer FS, Tizhoosh HR, Rahnamayan S (2014) Multi-resolution level sets with shape priors: a validation report for 2d segmentation of prostate gland in t2w mr images. J Digit Imaging 27(6):833–847

5. Alves RS, Tavares JMR (2015) Computer image registration techniques applied to nuclear medicine images. In: Computational and experimental biomedical sciences: methods and applications. Springer, pp 173–191

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