Contrastive learning of global and local features for medical image segmentation with limited annotations
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya - krishnabits001.github.io
In this work, we propose contrasting strategies to leverage domain-specific cues in defining
positive and negative pairs to leverage structural similarity across medical volumes. We also …
positive and negative pairs to leverage structural similarity across medical volumes. We also …
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani, E Konukoglu - arXiv preprint arXiv …, 2020 - arxiv.org
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani… - Proceedings of the 34th …, 2020 - dl.acm.org
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani, E Konukoglu - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
[引用][C] Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani, E Konukoglu - openreview.net
Contrastive learning of global and local features for medical image segmentation with limited
annotations | OpenReview OpenReview.net Login Open Peer Review. Open Publishing. Open …
annotations | OpenReview OpenReview.net Login Open Peer Review. Open Publishing. Open …
[PDF][PDF] Contrastive learning of global and local features for medical image segmentation with limited annotations
KCEEN Karani, E Konukoglu - proceedings.nips.cc
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Selfsupervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Selfsupervised learning (SSL) …
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani, E Konukoglu - arXiv, 2020 - research-collection.ethz.ch
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani… - Advances in Neural …, 2020 - proceedings.neurips.cc
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani… - Advances in Neural …, 2021 - research-collection.ethz.ch
A key requirement for the success of supervised deep learning is a large labeled dataset-a
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …
condition that is difficult to meet in medical image analysis. Self-supervised learning (SSL) …