Comparison of deep learning-based emission-only attenuation correction methods for positron emission tomography.
Purpose: This study aims to compare two approaches using only emission PET data and a convolution neural network (CNN) to correct the attenuation (μ) of the annihilation photons in PET. Methods: One of the approaches uses a CNN to generate μ-maps from the non-attenuation-corrected (NAC) PET images (...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 49; no. 6; pp. 1833 - 1843 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2022
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| Acceso en línea: | Ver este registro en EBSCOhost |