@inproceedings{c71b7bca1e6745a0bb9afc029922f61a,
title = "EVALUATING SELF-SUPERVISED LEARNING METHODS FOR DOWNSTREAM CLASSIFICATION OF NEOPLASIA IN BARRETT{\textquoteright}S ESOPHAGUS",
abstract = "A major problem in applying machine learning for the medical domain is the scarcity of labeled data, which results in the demand for methods that enable high-quality models trained with little to no labels. Self-supervised learning methods present a plausible solution to this problem, enabling the use of large sets of unlabeled data for model pretraining. In this study, multiple of these methods and training strategies are employed on a large dataset of endoscopic images from the gastrointestinal tract (GastroNet). The suitability of these methods is assessed for an intra-domain downstream classification task on a small endoscopic dataset, involving neoplasia in Barrett{\textquoteright}s esophagus. The classification performances are compared against pretraining on ImageNet and training from scratch. This yields promising results for domain-specific self-supervised methods, where super-resolution outperforms pretraining on ImageNet with a mean classification accuracy of 83.8% (cf. 79.2%). This implies that the large amounts of unlabeled data in hospitals could be employed in combination with self-supervised learning methods to improve models for downstream tasks.",
author = "S. Cornelissen and {van der Putten}, {J. A.} and Boers, {T. G. W.} and Jukema, {J. B.} and Fockens, {K. N.} and Bergman, {J. J. G. H. M.} and {van der Sommen}, F. and {de With}, {P. H. N.}",
year = "2021",
doi = "https://doi.org/10.1109/ICIP42928.2021.9506121",
language = "English",
volume = "2021-September",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "66--70",
booktitle = "2021 IEEE International Conference on Image Processing, ICIP 2021 - Proceedings",
note = "2021 IEEE International Conference on Image Processing, ICIP 2021 ; Conference date: 19-09-2021 Through 22-09-2021",
}