How Much Data are Enough? Investigating Dataset Requirements for Patch-Based Brain MRI Segmentation Tasks

arXiv:2404.03451v1 Announce Type: new
Abstract: Training deep neural networks reliably requires access to large-scale datasets. However, obtaining such datasets can be challenging, especially in the context of neuroimaging analysis tasks, where the cost associated with image acquisition and annotation can be prohibitive. To mitigate both the time and financial costs associated with model development, a clear understanding of the amount of data required to train a satisfactory model is crucial. This paper focuses on an early stage phase of deep …

abstract acquisition analysis annotation arxiv brain context cost cs.cv data dataset datasets however image mri networks neural networks neuroimaging requirements scale segmentation tasks training type