Higher effect sizes for the detection of accelerated brain volume loss and disability progression in multiple sclerosis using deep-learning DOI Creative Commons
Roland Opfer, Tjalf Ziemssen, Julia Krüger

и другие.

Computers in Biology and Medicine, Год журнала: 2024, Номер 183, С. 109289 - 109289

Опубликована: Окт. 18, 2024

Clinical validation of "BrainLossNet", a deep learning-based method for fast and robust estimation brain volume loss (BVL) from longitudinal T1-weighted MRI, the detection accelerated BVL in multiple sclerosis (MS) discrimination between MS patients with versus without disability progression.

Язык: Английский

Higher effect sizes for the detection of accelerated brain volume loss and disability progression in multiple sclerosis using deep-learning DOI Creative Commons
Roland Opfer, Tjalf Ziemssen, Julia Krüger

и другие.

Computers in Biology and Medicine, Год журнала: 2024, Номер 183, С. 109289 - 109289

Опубликована: Окт. 18, 2024

Clinical validation of "BrainLossNet", a deep learning-based method for fast and robust estimation brain volume loss (BVL) from longitudinal T1-weighted MRI, the detection accelerated BVL in multiple sclerosis (MS) discrimination between MS patients with versus without disability progression.

Язык: Английский

Процитировано

0