南加州大学首创的这种3D-CNN工具通过分析磁共振成像（MRI）扫描，以非侵入性的方式追踪大脑老化速度，提供了一种精确的方法来测量大脑随着时间的推移如何衰老。该模型有望成为理解、预防和治疗认知衰退及痴呆症的强大工具。

Forest City Diagnostic Imaging, LLC (Forest City) today announced that it has expanded its operational space, its diagnostic ...

The following is a summary of “Computer-aided diagnosis based on 3D deep convolutional neural network system using novel 3D ...

U-NET, a convolutional neural network architecture, demonstrates exceptional performance in brain tumour segmentation, ...

AI tool uses MRI scans to track the pace of brain changes, mapping anatomic variations in regional brain aging rates according to factors including sex and age.

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Researchers developed a groundbreaking method to track brain ageing pace using deep learning and MRI scans, providing ...

Traditional MRI analysis requires significant time and expertise, often leading to diagnosis and treatment planning delays.

The first-of-its-kind tool can non-invasively track the pace of brain changes by analyzing magnetic resonance imaging (MRI ... three-dimensional convolutional neural network (3D-CNN) offers ...

researchers examined the use of convolutional neural networks (CNNs) and transfer learning to improve brain tumor detection in magnetic resonance imaging (MRI) scans. Using CNNs pre-trained on ...