32 citations · 60 across the 2 of their papers we have counts for
2 papers
eess.IV2022★ 32 cited
USE-Evaluator: Performance Metrics for Medical Image Segmentation Models with Uncertain, Small or Empty Reference Annotations
Sophie Ostmeier, Brian Axelrod, Jeroen Bertels +6
Performance metrics for medical image segmentation models are used to measure the agreement between the reference annotation and the predicted segmentation. Usually, overlap metric…
physics.med-ph2020★ 28 cited
Improved Segmentation and Detection Sensitivity of Diffusion-Weighted Brain Infarct Lesions with Synthetically Enhanced Deep Learning
Christian Federau, Soren Christensen, Nino Scherrer +7
Purpose: To compare the segmentation and detection performance of a deep learning model trained on a database of human-labelled clinical diffusion-weighted (DW) stroke lesions to a…