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There are many clinical contexts which require accurate detection andsegmentation of all focal pathologies (e.g. lesions, tumours) in patientimages. In cases where there are a mix of small and large lesions, standardbinary cross entropy loss will result in better segmentation of large lesionsat the expense of missing small ones. Adjusting the operating point toaccurately detect all lesions generally leads to oversegmentation of largelesions. In this work, we propose a novel reweighing strategy to eliminate thisperformance gap, increasing small pathology detection performance whilemaintaining segmentation accuracy. We show that our reweighing strategy vastlyoutperforms competing strategies based on experiments on a large scale,multi-scanner, multi-center dataset of Multiple Sclerosis patient images.

Optimizing Operating Points for High Performance Lesion Detection and Segmentation Using Lesion Size Reweighting