Primary tumour type impacts 3D U-Net for [18F]FDG PET lesion segmentation performance in cases of lung cancer, melanoma, and lymphoma

Primary tumour type impacts 3D U-Net for [¹⁸F]FDG PET lesion segmentation performance in cases of lung cancer, melanoma, and lymphoma

M. Sobral, M. Oliveira, C. Constantino, F. Oliveira, N. Matela, D. C. Costa

Resultado de pesquisa › revisão de pares

Idioma original	English
Páginas (de-até)	S271-S272
Número de páginas	2
Revista	European Journal of Nuclear Medicine and Molecular Imaging
Volume	50
Número de emissão	SUPPL 1
Estado da publicação	Publicado - set. 2023

Este resultado contribui para o(s) seguinte(s) Objetivo(s) de Desenvolvimento Sustentável

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title = "Primary tumour type impacts 3D U-Net for [18F]FDG PET lesion segmentation performance in cases of lung cancer, melanoma, and lymphoma",

author = "M. Sobral and M. Oliveira and C. Constantino and F. Oliveira and N. Matela and Costa, {D. C.}",

year = "2023",

month = sep,

language = "English",

volume = "50",

pages = "S271--S272",

journal = "European Journal of Nuclear Medicine and Molecular Imaging",

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publisher = "Springer Verlag",

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TY - JOUR

T1 - Primary tumour type impacts 3D U-Net for [18F]FDG PET lesion segmentation performance in cases of lung cancer, melanoma, and lymphoma

AU - Sobral, M.

AU - Oliveira, M.

AU - Constantino, C.

AU - Oliveira, F.

AU - Matela, N.

AU - Costa, D. C.

PY - 2023/9

Y1 - 2023/9

M3 - Meeting Abstract

SN - 1619-7070

VL - 50

SP - S271-S272

JO - European Journal of Nuclear Medicine and Molecular Imaging

JF - European Journal of Nuclear Medicine and Molecular Imaging

IS - SUPPL 1

ER -