Attenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging.

Gong, Kuang; Han, Paul Kyu; Johnson, Keith A; El Fakhri, Georges; Ma, Chao; Li, Quanzheng

Gong, Kuang; Han, Paul Kyu; Johnson, Keith A; El Fakhri, Georges; Ma, Chao; Li, Quanzheng.

Afiliación

Gong K; Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
Han PK; Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
Johnson KA; Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
El Fakhri G; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
Ma C; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Li Q; Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.

Eur J Nucl Med Mol Imaging ; 48(5): 1351-1361, 2021 05.

Article en En | MEDLINE | ID: mdl-33108475

Asunto(s)

Aprendizaje Profundo; Humanos; Procesamiento de Imagen Asistido por Computador; Imagen por Resonancia Magnética; Imagen Multimodal; Tomografía de Emisión de Positrones; Tomografía Computarizada por Rayos X

Palabras clave

Attenuation correction; Convolutional neural network; Deep learning; PET/MR; UTE/multi-echo Dixon

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Límite: Humans Idioma: En Revista: Eur J Nucl Med Mol Imaging Asunto de la revista: MEDICINA NUCLEAR Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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