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Deep Learning Methods for Tumor Segmentation and Detection in X-Ray Breast Imaging

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dc.contributor.author CHATZAKIS, D.
dc.contributor.author DERMITZAKIS, A.
dc.contributor.author PALLIKARAKIS, N.
dc.date.accessioned 2021-11-15T14:06:07Z
dc.date.available 2021-11-15T14:06:07Z
dc.date.issued 2021
dc.identifier.citation CHATZAKIS, D., DERMITZAKIS, A., PALLIKARAKIS, N. Deep Learning Methods for Tumor Segmentation and Detection in X-Ray Breast Imaging. In: ICNMBE-2021: the 5th International Conference on Nanotechnologies and Biomedical Engineering, November 3-5, 2021: Program and abstract book. Chişinău, 2021, p. 124. ISBN 978-9975-72-592-7. en_US
dc.identifier.isbn 978-9975-72-592-7
dc.identifier.uri http://repository.utm.md/handle/5014/18067
dc.description Only Abstract. en_US
dc.description.abstract Recently there have been a series of machine learning methods or deep learning architectures that have been developed and used in the field medical imaging. In this study, we focus on the use of AI in the field of breast imaging and the methods with the highest accuracy results for breast tumor segmentation and classification are presented, achieving robust results in detection. Extensive research which included more than 150 related published papers was performed, containing results published between 2016 to 2020 resulting in a review of 4 selected models all at the forefront of current progress. en_US
dc.language.iso en en_US
dc.publisher Universitatea Tehnică a Moldovei en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject tumor segmentation en_US
dc.subject tumor detection en_US
dc.subject X-Ray breast imaging en_US
dc.title Deep Learning Methods for Tumor Segmentation and Detection in X-Ray Breast Imaging en_US
dc.type Article en_US


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