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Table 1 A summary of the experiments performed in this study

From: Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study

Experiment Dataset Size GT Seg. Method
A Hammersmith 100 Yes RF
B UKBB-2964 4805 Yes RF and CNN
C UKBB-18545 7250 No Multi-Atlas
  1. Experiment A uses data from an internal dataset which is segmented with a multi-atlas segmentation approach and manually validated by experts at Hammersmith Hospital, London. These manual validations are counted as ‘ground truth’ (GT) and 100 of them are taken for the reference set used in all experiments. UKBB datasets are shown with their application numbers. In experiment C we segment with both random forests (RF) and a convolutional neural network (CNN). In C the CNN from Bai [4] is used