activity
20192022
most citedCrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

99 citations · 116 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2022★ 17 cited

Biomedical image analysis competitions: The state of current participation practice

Matthias Eisenmann, Annika Reinke, Vivienn Weru +352

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…

eess.IV2022★ 99 cited

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

Reuben Dorent, Aaron Kujawa, Marina Ivory +37

Domain Adaptation (DA) has recently raised strong interests in the medical imaging community. While a large variety of DA techniques has been proposed for image segmentation, most…

eess.IV2021

C-MADA: Unsupervised Cross-Modality Adversarial Domain Adaptation framework for medical Image Segmentation

Maria Baldeon-Calisto, Susana K. Lai-Yuen

Deep learning models have obtained state-of-the-art results for medical image analysis. However, when these models are tested on an unseen domain there is a significant performance…

cs.CV2020

Neural Architecture Search with an Efficient Multiobjective Evolutionary Framework

Maria Baldeon Calisto, Susana Lai-Yuen

Deep learning methods have become very successful at solving many complex tasks such as image classification and segmentation, speech recognition and machine translation. Neverthel…

eess.IV2019

Self-Adaptive 2D-3D Ensemble of Fully Convolutional Networks for Medical Image Segmentation

Maria G. Baldeon Calisto, Susana K. Lai-Yuen

Segmentation is a critical step in medical image analysis. Fully Convolutional Networks (FCNs) have emerged as powerful segmentation models achieving state-of-the-art results in va…