Deep Learning based Segmentation for Multi MR Imaging Protocols using Transfer Learning for PET Attenuation Correction.

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/22251

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DC Field	Value	Language
dc.contributor.author	Mecheter, I	-
dc.contributor.author	Amira, A	-
dc.contributor.author	Abbod, M	-
dc.contributor.author	Zaidi, H	-
dc.date.accessioned	2021-02-10T18:32:27Z	-
dc.date.available	2020	-
dc.date.available	2021-02-10T18:32:27Z	-
dc.date.issued	2021-01-05	-
dc.identifier.citation	Mecheter, I., Amira, A., Abbod, M. and Zaidi, H. (2021) 'Deep Learning based Segmentation for Multi MR Imaging Protocols using Transfer Learning for PET Attenuation Correction.', Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia, 1-4 Dec. 2020, pp. 2516 - 2520. doi: 10.1109/SSCI47803.2020.9308177.	en_US
dc.identifier.isbn	978-1-7281-2547-3	-
dc.identifier.uri	http://bura.brunel.ac.uk/handle/2438/22251	-
dc.format.extent	2516 - 2520	-
dc.language.iso	en_US	en_US
dc.publisher	IEEE	en_US
dc.subject	magnetic resonance imaging	en_US
dc.subject	segmentation	en_US
dc.subject	PET attenuation correction	en_US
dc.subject	deep learning	en_US
dc.subject	transfer learning	en_US
dc.title	Deep Learning based Segmentation for Multi MR Imaging Protocols using Transfer Learning for PET Attenuation Correction.	en_US
dc.type	Conference Paper	en_US
dc.relation.isPartOf	SSCI	-
Appears in Collections:	Dept of Electronic and Electrical Engineering Research Papers

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