Active learning for medical image segmentation with stochastic batches

1 code implementation • 18 Jan 2023 • Mélanie Gaillochet, Christian Desrosiers, Hervé Lombaert

The performance of learning-based algorithms improves with the amount of labelled data used for training.

Active Learning Image Segmentation +3

TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation

2 code implementations • 16 Jan 2023 • Mélanie Gaillochet, Christian Desrosiers, Hervé Lombaert

This paper proposes Test-time Augmentation for Active Learning (TAAL), a novel semi-supervised active learning approach for segmentation that exploits the uncertainty information offered by data transformations.

Active Learning Image Segmentation +2

Joint reconstruction and bias field correction for undersampled MR imaging

no code implementations • 26 Jul 2020 • Mélanie Gaillochet, Kerem C. Tezcan, Ender Konukoglu

To this end, we use an unsupervised learning based reconstruction algorithm as our basis and combine it with a N4-based bias field estimation method, in a joint optimization scheme.