Automated Segmentation of Breast Skin for Early Cancer Diagnosis: A Multi-otsu Region Growing Approach for Detecting Skin Thickness Variations-Reference-Cited by-同舟云学术

Automated Segmentation of Breast Skin for Early Cancer Diagnosis: A Multi-otsu Region Growing Approach for Detecting Skin Thickness Variations

Published:2023-10-26 Issue: Volume: Page:211-221
ISSN:1680-0737
Container-title:IFMBE Proceedings
language:
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Author:

Medina-Ramos Luis Antonio^ORCID,Toriz-Vázquez Alfonso^ORCID,Hernández-Rodríguez Yazmín Mariela^ORCID,Bayareh-Mancilla Rafael^ORCID,Cigarroa-Mayorga Oscar Eduardo^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-46933-6_23

Reference19 articles.

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3. Marmot, M.G., Altman, D.G., Cameron, D.A., Dewar, J.A., Thompson, S.G., Wilcox, M.: The benefits and harms of breast cancer screening: an independent review: a report jointly commissioned by Cancer Research UK and the Department of Health (England) October 2012. Br. J. Cancer 108, 2205 (2013). https://doi.org/10.1038/BJC.2013.177

4. Kim, M.Y., Choi, N.: Mammographic and ultrasonographic features of triple-negative breast cancer: a comparison with other breast cancer subtypes. Acta radiol. 54 (2013). https://doi.org/10.1177/0284185113488580

5. Pediconi, F., et al.: Breast imaging and cancer diagnosis during the COVID-19 pandemic: recommendations from the Italian College of Breast Radiologists by SIRM. Radiologia Medica. 125 (2020). https://doi.org/10.1007/s11547-020-01254-3

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