Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI

Daniel M. Lang*, Eli Schwartz, Cosmin I. Bercea, Raja Giryes, Julia A. Schnabel

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Mammography is commonly used as an imaging technique in breast cancer screening but comes with the disadvantage of a high overdiagnosis rate and low sensitivity in dense tissue. dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) features higher sensitivity but requires time consuming dynamic imaging and injection of contrast media, limiting the capability of the technique as a widespread screening method. In this work, we extend the masked autoencoder (MAE) approach to perform anomaly detection on volumetric, multispectral MRI. This new model, coined masked autoencoder for medical imaging (MAEMI), is trained on two non-contrast enhanced breast MRI sequences, aiming at lesion detection without the need for intravenous injection of contrast media and temporal image acquisition, paving the way for more widespread use of MRI in breast cancer diagnosis. During training, only non-cancerous images are presented to the model, with the purpose of localizing anomalous tumor regions during test time. We use a public dataset for model development. Performance of the architecture is evaluated in reference to subtraction images created from DCE-MRI. Code has been made publicly available: https://github.com/LangDaniel/MAEMI.

Original languageEnglish
Title of host publicationCancer Prevention Through Early Detection - 2nd International Workshop, CaPTion 2023, Held in Conjunction with MICCAI 2023, Proceedings
EditorsSharib Ali, Fons van der Sommen, Maureen van Eijnatten, Iris Kolenbrander, Bartłomiej W. Papież, Yueming Jin
PublisherSpringer Science and Business Media Deutschland GmbH
Pages55-67
Number of pages13
ISBN (Print)9783031453496
DOIs
StatePublished - 2023
Event2nd International Workshop on Cancer Prevention through early detecTion, CaPTion 2023 - Vancover, Canada
Duration: 12 Oct 202312 Oct 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14295 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Workshop on Cancer Prevention through early detecTion, CaPTion 2023
Country/TerritoryCanada
CityVancover
Period12/10/2312/10/23

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