16 citations · 37 across the 3 of their papers we have counts for
3 papers
eess.IV2021★ 16 cited
Semi-supervised learning for generalizable intracranial hemorrhage detection and segmentation
Emily Lin, Esther Yuh
Purpose: To develop and evaluate a semi-supervised learning model for intracranial hemorrhage detection and segmentation on an out-of-distribution head CT evaluation set. Materials…
cs.CV2018★ 9 cited
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection
Weicheng Kuo, Christian Häne, Esther Yuh +2
Deep learning for clinical applications is subject to stringent performance requirements, which raises a need for large labeled datasets. However, the enormous cost of labeling med…
cs.CV2018★ 12 cited
PatchFCN for Intracranial Hemorrhage Detection
Weicheng Kuo, Christian Häne, Esther Yuh +2
This paper studies the problem of detecting and segmenting acute intracranial hemorrhage on head computed tomography (CT) scans. We propose to solve both tasks as a semantic segmen…