Influence of Magnification in Deep Learning Aided Image Segmentation in Histological Digital Image Analysis

The use of digital pathology has grown significantly for both healthcare and research purposes in recent years. With this comes opportunity to develop systems supported by computer vision (CV) and artificial intelligence (AI), with the potential to improve patient management and quality of care. The accessibility of CV and AI toolboxes have resulted in the rapid application of image analysis in this domain driven by accuracy related metrics. However, in this short paper we illustrate common pitfalls in the field through a semantic segmentation task, specifically how magnification can influence training data quality and demonstrate how this can ultimately affect model robustness.