Self-supervised learning for medical image analysis using image context restoration.

Medical Image Analysis
Liang ChenDaniel Rueckert

Abstract

Machine learning, particularly deep learning has boosted medical image analysis over the past years. Training a good model based on deep learning requires large amount of labelled data. However, it is often difficult to obtain a sufficient number of labelled images for training. In many scenarios the dataset in question consists of more unlabelled images than labelled ones. Therefore, boosting the performance of machine learning models by using unlabelled as well as labelled data is an important but challenging problem. Self-supervised learning presents one possible solution to this problem. However, existing self-supervised learning strategies applicable to medical images cannot result in significant performance improvement. Therefore, they often lead to only marginal improvements. In this paper, we propose a novel self-supervised learning strategy based on context restoration in order to better exploit unlabelled images. The context restoration strategy has three major features: 1) it learns semantic image features; 2) these image features are useful for different types of subsequent image analysis tasks; and 3) its implementation is simple. We validate the context restoration strategy in three common problems in medical imag...Continue Reading

References

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Citations

Sep 15, 2020·JCO Clinical Cancer Informatics·Matthew NagyAziz Nazha
Aug 9, 2020·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Max ToropUlugbek S Kamilov
Apr 5, 2020·Brain Sciences·Ping CaoZuping Zhang
Dec 2, 2020·Medical Image Analysis·Ozan Ciga, Anne L Martel
Jan 5, 2021·Informatics in Medicine Unlocked·Amir Hossein PanahiAlireza Rezaee
Nov 15, 2020·Medical Image Analysis·Zongwei ZhouJianming Liang
Jan 9, 2021·Journal of Neuroscience Methods·Eichi TakayaSatoshi Kurihara
Jan 13, 2021·Journal of Personalized Medicine·Oliwia KotelukAndrzej Mackiewicz
Oct 30, 2020·Forensic Science International : Synergy·Carlos A Peña-SolórzanoMatthew R Dimmock
Mar 14, 2021·Nature Reviews. Cardiology·Maxime SermesantNicholas Ayache
Apr 2, 2021·Biotechnology Advances·Parminder S ReelEmily Jefferson
Apr 14, 2021·Scientific Reports·Steven KorevaarAlireza Bab-Hadiashar
May 1, 2021·Diagnostics·Rima HajjoAlexander Tropsha
May 7, 2021·International Journal of Computer Assisted Radiology and Surgery·Alice M L SantilliParvin Mousavi
May 14, 2021·Computers in Biology and Medicine·Chi ZhangPengwei Wang
May 13, 2021·Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)·Ana Barragán-MonteroJohn A Lee
Jun 15, 2021·Microscopy Research and Technique·Heba M EmaraFathi E Abd El-Samie
Jul 1, 2021·European Journal of Hybrid Imaging·Hossein Arabi, Habib Zaidi
Jun 14, 2021·International Journal of Computer Assisted Radiology and Surgery·Fernando Pérez-GarcíaSébastien Ourselin
Jul 27, 2021·Computer Methods and Programs in Biomedicine·Fernando Pérez-GarcíaSébastien Ourselin
Jul 16, 2021·Skeletal Radiology·Florian A Huber, Roman Guggenberger
Aug 31, 2021·Medical Image Analysis·Laurent Lejeune, Raphael Sznitman

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