Generalized Probabilistic U-Net for Medical Image Segementation

Ishaan Bhat, Josien P.W. Pluim, Hugo J. Kuijf

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)

Samenvatting

We propose the Generalized Probabilistic U-Net, which extends the Probabilistic U-Net [14] by allowing more general forms of the Gaussian distribution as the latent space distribution that can better approximate the uncertainty in the reference segmentations. We study the effect the choice of latent space distribution has on capturing the uncertainty in the reference segmentations using the LIDC-IDRI dataset. We show that the choice of distribution affects the sample diversity of the predictions and their overlap with respect to the reference segmentations. For the LIDC-IDRI dataset, we show that using a mixture of Gaussians results in a statistically significant improvement in the generalized energy distance (GED) metric with respect to the standard Probabilistic U-Net. We have made our implementation available at https://github.com/ishaanb92/GeneralizedProbabilisticUNet.

Originele taal-2Engels
TitelUncertainty for Safe Utilization of Machine Learning in Medical Imaging - 4th International Workshop, UNSURE 2022, Held in Conjunction with MICCAI 2022, Proceedings
RedacteurenCarole H. Sudre, Carole H. Sudre, Christian F. Baumgartner, Adrian Dalca, Adrian Dalca, William M. Wells III, Chen Qin, Ryutaro Tanno, Koen Van Leemput, Koen Van Leemput, William M. Wells III
UitgeverijSpringer
Pagina's113-124
Aantal pagina's12
ISBN van geprinte versie9783031167485
DOI's
StatusGepubliceerd - 2022
Evenement4th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2022, held in conjunction with 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022 - Singapore, Singapore
Duur: 18 sep. 202218 sep. 2022

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13563 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Congres

Congres4th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2022, held in conjunction with 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022
Land/RegioSingapore
StadSingapore
Periode18/09/2218/09/22

Bibliografische nota

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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