@inproceedings{627fc7d3f0a143cf91543d833d5c63de,
title = "Unsupervised deep novelty detection: Application to muscle ultrasound and myositis screening",
abstract = "This study investigates unsupervised novelty detection (ND) for screening of rare myopathies and specifically myositis. To support this study we developed from the ground up a novel and fully annotated dataset consisting of 3586 images taken of eighty nine individuals obtained under informed consent during 2016-2017. We developed and compared performance for several ND methods leveraging deep feature embeddings, utilizing generative as well as discriminative deep learning approaches for embeddings, and using various novelty scores. We carried out several performance comparisons including with a clinician, supervised binary classification approaches, and a generative method, demonstrating that our best performing approach is competitive with human performance and other best of breed algorithms.",
keywords = "Deep embeddings, Myopathy, Myositis, Novelty detection, Unsupervised learning",
author = "P. Burlina and N. Joshi and S. Billings and Wang, {I. J.} and J. Albayda",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 ; Conference date: 08-04-2019 Through 11-04-2019",
year = "2019",
month = apr,
doi = "10.1109/ISBI.2019.8759565",
language = "English (US)",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "1910--1914",
booktitle = "ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging",
}