Do we really need all these preprocessing steps in brain MRI segmentation?
Ekaterina Kondrateva, Polina Druzhinina, Anvar Kurmukov
Magnetic resonance imaging (MRI) data is heterogeneous due to the differences in device manufacturers, scanning protocols, and inter-subject variability. Although preprocessing pipeline standardizes image appearance, its influence on the quality of image segmentation on deep neural networks (DNN) has never been rigorously studied. Here we report a comprehensive study of multimodal MRI brain cancer image segmentation on TCIA-GBM open-source dataset. Our results that the most popular standardization steps add no value to artificial neural network performance; moreover, preprocessing can hamper model performance. We show that the only essential transformation for accurate analysis is the unification of voxel spacing across the dataset.
Wednesday 6th July
Poster Session 1.2 - onsite 11:00 - 12:00, virtual 15:20 - 16:20 (UTC+2)