Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy

A survey on transfer learning

Sinno Jialin Pan and Qiang Yang · 2010

Earlier work this paper cites.

Active supervised domain adaptation

Avishek Saha, Piyush Rai, Hal Daumé, Suresh Venkatasubramanian, and Scott L DuVall · 2011

Earlier work this paper cites.

Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks

Dong-Hyun Lee · 2013

Earlier work this paper cites.

Cnn features off-the-shelf: an astounding baseline for recognition

Ali Sharif Razavian, Hossein Azizpour, Josephine Sullivan, and Stefan Carlsson · 2014

Earlier work this paper cites.

Weighting training images by maximizing distribution similarity for supervised segmentation across scanners

Annegreet van Opbroek, Meike W Vernooij, M Arfan Ikram, and Marleen de Bruijne · 2015

Cited alongside, same era.

Domain adaptation for learning from label proportions using self-training

Ehsan Mohammady Ardehaly and Aron Culotta · 2016

Cited alongside, same era.

Dalsa: domain adaptation for supervised learning from sparsely annotated mr images

Michael Goetz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Koethe, Jens Kleesiek, Bram Stieltjes, and Klaus H Maier-Hein · 2016

Cited alongside, same era.

Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning

Hoo-Chang Shin, Holger R Roth, Mingchen Gao, Le Lu, Ziyue Xu, Isabella Nogues, Jianhua Yao, Daniel Mollura, and Ronald M Summers · 2016

Cited alongside, same era.

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia Newcombe, Joanna Simpson, Andrew Kane, David Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, and Ben Glocker

Cited in the paper.

Efficient multi-scale 3d cnn with fully connected crf for accurate brain lesion segmentation

Konstantinos Kamnitsas, Christian Ledig, Virginia FJ Newcombe, Joanna P Simpson, Andrew D Kane, David K Menon, Daniel Rueckert, and Ben Glocker

Cited in the paper.

Convolutional neural networks for medical image analysis: full training or fine tuning?

Nima Tajbakhsh, Jae Y Shin, Suryakanth R Gurudu, R Todd Hurst, Christopher B Kendall, Michael B Gotway, and Jianming Liang · 2016

Later among the works it cites.

Transfer learning for domain adaptation in mri: Application in brain lesion segmentation

Original

Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur, Nico Karssemeijer, Elena Marchiori, Mehran Pesteie, Charles RG Guttmann, Frank-Erik de Leeuw, Clare M Tempany, Bram van Ginneken, et al · 2017

Later among the works it cites.

Reverse classification accuracy: Predicting segmentation performance in the absence of ground truth

Vanya V Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O Aboagye, Andrea G Rockall, Daniel Rueckert, and Ben Glocker · 2017

Later among the works it cites.

Fine-tuning convolutional neural networks for biomedical image analysis: actively and incrementally

Zongwei Zhou, Jae Shin, Lei Zhang, Suryakanth Gurudu, Michael Gotway, and Jianming Liang · 2017

Later among the works it cites.