most citedLabel Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets With Domain Shift and Partial Labelling

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2026

Detecting and refurbishing ground truth errors during training of deep learning-based echocardiography segmentation models

Iman Islam, Bram Ruijsink, Andrew J. Reader +1

Deep learning-based medical image segmentation typically relies on ground truth (GT) labels obtained through manual annotation, but these can be prone to random errors or systemati…

cs.CV2024★ 3 cited

Label Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets With Domain Shift and Partial Labelling

Iman Islam, Esther Puyol-Antón, Bram Ruijsink +2

Echocardiography (echo) is the first imaging modality used when assessing cardiac function. The measurement of functional biomarkers from echo relies upon the segmentation of cardi…