Automation of a Rule-based Workflow to Estimate Age from Brain MR Imaging of Infants and Children Up to 2 Years Old Using Stacked Deep Learning

Purpose: Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted images (T2WIs) has been widely used in radiology. T...

Descripción completa

Detalles Bibliográficos
Autores principales: Wada, Akihiko, Saito, Yuya, Fujita, Shohei, Irie, Ryusuke, Akashi, Toshiaki, Sano, Katsuhiro, Kato, Shinpei, Ikenouchi, Yutaka, Hagiwara, Akifumi, Sato, Kanako, Tomizawa, Nobuo, Hayakawa, Yayoi, Kikuta, Junko, Kamagata, Koji, Suzuki, Michimasa, Hori, Masaaki, Nakanishi, Atsushi, Aoki, Shigeki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society for Magnetic Resonance in Medicine 2021
Materias:
Major Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9849414/
https://www.ncbi.nlm.nih.gov/pubmed/34897147
http://dx.doi.org/10.2463/mrms.mp.2021-0068

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9849414/
https://www.ncbi.nlm.nih.gov/pubmed/34897147
http://dx.doi.org/10.2463/mrms.mp.2021-0068

Ejemplares similares