A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
Neuroanatomical segmentation in T1-weighted magnetic resonance imaging of the brain is a prerequisite for quantitative morphological measurements, as well as an essential element in general pre-processing pipelines. While recent fully automated segmentation methods based on convolutional neural networks have shown great potential, these methods nonetheless suffer from severe performance degradation when there are mismatches between training (source) and testing (target) domains (e.g. due todoi:10.1101/845537 fatcat:nn4dpm43qrcgjmklarrqfrqpvy