{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:28:33Z","timestamp":1772252913720,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,22]],"date-time":"2021-10-22T00:00:00Z","timestamp":1634860800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007891","name":"Ryerson University","doi-asserted-by":"publisher","award":["Internal Grant"],"award-info":[{"award-number":["Internal Grant"]}],"id":[{"id":"10.13039\/100007891","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Deep learning (DL) algorithms have become an increasingly popular choice for image classification and segmentation tasks; however, their range of applications can be limited. Their limitation stems from them requiring ample data to achieve high performance and adequate generalizability. In the case of clinical imaging data, images are not always available in large quantities. This issue can be alleviated by using data augmentation (DA) techniques. The choice of DA is important because poor selection can possibly hinder the performance of a DL algorithm. We propose a DA policy search algorithm that offers an extended set of transformations that accommodate the variations in biomedical imaging datasets. The algorithm makes use of the efficient and high-dimensional optimizer Bi-Population Covariance Matrix Adaptation Evolution Strategy (BIPOP-CMA-ES) and returns an optimal DA policy based on any input imaging dataset and a DL algorithm. Our proposed algorithm, Medical Augmentation (Med-Aug), can be implemented by other researchers in related medical DL applications to improve their model\u2019s performance. Furthermore, we present our found optimal DA policies for a variety of medical datasets and popular segmentation networks for other researchers to use in related tasks.<\/jats:p>","DOI":"10.3390\/s21217018","type":"journal-article","created":{"date-parts":[[2021,10,24]],"date-time":"2021-10-24T22:07:11Z","timestamp":1635113231000},"page":"7018","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Medical Augmentation (Med-Aug) for Optimal Data Augmentation in Medical Deep Learning Networks"],"prefix":"10.3390","volume":"21","author":[{"given":"Justin","family":"Lo","sequence":"first","affiliation":[{"name":"Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada"},{"name":"Institute for Biomedical Engineering, Science and Technology (iBEST) at Ryerson University & St. Michael\u2019s Hospital, Toronto, ON M5B 1T8, Canada"}]},{"given":"Jillian","family":"Cardinell","sequence":"additional","affiliation":[{"name":"Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada"},{"name":"Institute for Biomedical Engineering, Science and Technology (iBEST) at Ryerson University & St. Michael\u2019s Hospital, Toronto, ON M5B 1T8, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3234-3732","authenticated-orcid":false,"given":"Alejo","family":"Costanzo","sequence":"additional","affiliation":[{"name":"Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada"},{"name":"Institute for Biomedical Engineering, Science and Technology (iBEST) at Ryerson University & St. Michael\u2019s Hospital, Toronto, ON M5B 1T8, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9977-3131","authenticated-orcid":false,"given":"Dafna","family":"Sussman","sequence":"additional","affiliation":[{"name":"Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada"},{"name":"Institute for Biomedical Engineering, Science and Technology (iBEST) at Ryerson University & St. Michael\u2019s Hospital, Toronto, ON M5B 1T8, Canada"},{"name":"The Keenan Research Centre for Biomedical Science, St. Michael\u2019s Hospital, Toronto, ON M5B 1T8, Canada"},{"name":"Department of Obstetrics and Gynecology, Faculty of Medicine, University of Toronto, Toronto, ON M5G 1E2, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-019-0197-0","article-title":"A survey on Image Data Augmentation for Deep Learning","volume":"6","author":"Shorten","year":"2019","journal-title":"J. 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