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Kazeminia, S. ; Brezik, M. ; Shetab Boushehri, S. ; Marr, C.

A data-driven solution for the cold start problem in biomedical image classification.

In: (Proceedings - International Symposium on Biomedical Imaging, 27-30 May 2024, Athen). 345 E 47th St, New York, Ny 10017 Usa: Ieee, 2024. DOI: 10.1109/ISBI56570.2024.10635886 (Proceedings - International Symposium on Biomedical Imaging)
DOI
The demand for large quantities of high-quality annotated images poses a significant bottleneck for developing effective deep learning-based classifiers in the biomedical domain. We present a simple yet powerful solution to the cold start problem, i.e., selecting the most informative data for annotation within an unlabeled dataset. Our framework consists of three key components: (i) A self-supervised encoder to construct meaningful representations of unlabeled data, (ii) a sampling method selecting the most representative data points for annotation, and (iii) a classifier head using model ensembling to overcome the lack of validation data. We test our approach on four challenging public biomedical datasets. Our strategy outperforms the state-of-the-art approach in detecting the representative data points in all datasets and achieves a 7% improvement on a leukemia blood cell classification task. Our work offers a practical and efficient solution to the challenges associated with tedious and costly, high-quality data annotations in the biomedical field. We make our framework's code publicly available on https://github.com/marrlab/initial-data-point-selection.
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Publikationstyp Artikel: Konferenzbeitrag
Korrespondenzautor
ISSN (print) / ISBN 1945-7928
e-ISSN 1945-8452
Konferenztitel Proceedings - International Symposium on Biomedical Imaging
Konferzenzdatum 27-30 May 2024
Konferenzort Athen
Verlag Ieee
Verlagsort 345 E 47th St, New York, Ny 10017 Usa
Nichtpatentliteratur Publikationen
Institut(e) Institute of AI for Health (AIH)
Förderungen Hightech Agenda Bayern
European Research Council (ERC) under the European Union
F. Hoffmannla Roche LTD
Helmholtz Association under the joint research school 'Munich School for Data Science -MUDS'