Effect of latent space distribution on the segmentation of images with multiple annotations
Ishaan Bhat1
, Josien P.W. Pluim2, Max A. Viergever1, Hugo J. Kuijf1
1: Image Sciences Institute, University Medical Center Utrecht, The Netherlands, 2: Department of Biomedical Engineering, Eindhoven University of Technology, The Netherlands
Publication date: 2023/04/30
https://doi.org/10.59275/j.melba.2023-18ae
Abstract
We propose the Generalized Probabilistic U-Net, which extends the Probabilistic U-Net 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 variation in the reference segmentations for lung tumors and white matter hyperintensities in the brain. We show that the choice of distribution affects the sample diversity of the predictions and their overlap with respect to the reference segmentations. We have made our implementation available at https://github.com/ishaanb92/GeneralizedProbabilisticUNet
Keywords
Deep learning · Image segmentation · Uncertainty estimation · Bayesian machine learning
Bibtex
@article{melba:2023:005:bhat,
title = "Effect of latent space distribution on the segmentation of images with multiple annotations",
author = "Bhat, Ishaan and Pluim, Josien P.W. and Viergever, Max A. and Kuijf, Hugo J.",
journal = "Machine Learning for Biomedical Imaging",
volume = "2",
issue = "UNSURE2022 special issue",
year = "2023",
pages = "151--171",
issn = "2766-905X",
doi = "https://doi.org/10.59275/j.melba.2023-18ae",
url = "https://melba-journal.org/2023:005"
}
RIS
TY - JOUR
AU - Bhat, Ishaan
AU - Pluim, Josien P.W.
AU - Viergever, Max A.
AU - Kuijf, Hugo J.
PY - 2023
TI - Effect of latent space distribution on the segmentation of images with multiple annotations
T2 - Machine Learning for Biomedical Imaging
VL - 2
IS - UNSURE2022 special issue
SP - 151
EP - 171
SN - 2766-905X
DO - https://doi.org/10.59275/j.melba.2023-18ae
UR - https://melba-journal.org/2023:005
ER -