Generalisability of Automated CNN-based Renal Segmentation for Multi-Vendor Studies

Abstract

Manual segmentation of the kidneys is very time consuming and reader dependent, this renders measurements of total kidney volume (TKV) in large multi-site studies impractical. Here we use a convolutional neural network (CNN), trained on data from a single MRI vendor, to segment the kidneys of volunteers scanned with a harmonised FSE image protocol on MR scanners from three different vendors (GE, Philips and Siemens). The kidneys were manually segmented by two readers, both of which demonstrated a significant difference in TKV across vendors; no significant difference in TKV was found in the segmentations produced by the CNN.