English

Contour Dice loss for structures with Fuzzy and Complex Boundaries in Fetal MRI

Image and Video Processing 2022-09-27 v1 Computer Vision and Pattern Recognition

Abstract

Volumetric measurements of fetal structures in MRI are time consuming and error prone and therefore require automatic segmentation. Placenta segmentation and accurate fetal brain segmentation for gyrification assessment are particularly challenging because of the placenta fuzzy boundaries and the fetal brain cortex complex foldings. In this paper, we study the use of the Contour Dice loss for both problems and compare it to other boundary losses and to the combined Dice and Cross-Entropy loss. The loss is computed efficiently for each slice via erosion, dilation and XOR operators. We describe a new formulation of the loss akin to the Contour Dice metric. The combination of the Dice loss and the Contour Dice yielded the best performance for placenta segmentation. For fetal brain segmentation, the best performing loss was the combined Dice with Cross-Entropy loss followed by the Dice with Contour Dice loss, which performed better than other boundary losses.

Keywords

Cite

@article{arxiv.2209.12232,
  title  = {Contour Dice loss for structures with Fuzzy and Complex Boundaries in Fetal MRI},
  author = {Bella Specktor Fadida and Bossmat Yehuda and Daphna Link Sourani and Liat Ben Sira and Dafna Ben Bashat and Leo Joskowicz},
  journal= {arXiv preprint arXiv:2209.12232},
  year   = {2022}
}

Comments

15 pages, 7 figures, Accepted to ECCV-MCV 2022: https://mcv-workshop.github.io/