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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