Introduction: Since 2002, when we published our article about the anterior perforated substance (APS), the knowledge about the region has grown enormously.
Objective: To make a better description of the anatomy of the zone with new dissection material added to the previous, to sustain the anatomical analysis of the MRI employing the SPACE sequence, interacting with our imagenology colleagues. Especially, we aim to identify and topographically localize by MRI the principal structures in APS-substantia innominata (SI).
Objective: To automate the segmentation of whole liver parenchyma on multi-echo chemical shift encoded (MECSE) MR examinations using convolutional neural networks (CNNs) to seamlessly quantify precise organ-related imaging biomarkers such as the fat fraction and iron load.
Methods: A retrospective multicenter collection of 183 MECSE liver MR examinations was conducted. An encoder-decoder CNN was trained (107 studies) following a 5-fold cross-validation strategy to improve the model performance and ensure lack of overfitting.