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

arXiv: https://arxiv.org/abs/2209.12232 · HTML: https://mlsanity.com/paper/2209.12232/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 28 references that are in the map.
- First posted on arXiv 25 Sep 2022.

## Builds on (most cited first, 7 of 7)

- [Boundary loss for highly unbalanced segmentation](https://mlsanity.com/paper/1812.07032/) (2018)
- [Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks](https://mlsanity.com/paper/1904.10030/) (2019)
- [Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy](https://mlsanity.com/paper/1809.04430/) (2018)
- [Distance Map Loss Penalty Term for Semantic Segmentation](https://mlsanity.com/paper/1908.03679/) (2019)
- [Fetal Brain Tissue Annotation and Segmentation Challenge Results](https://mlsanity.com/paper/2204.09573/) (2022)
- [Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning](https://mlsanity.com/paper/1710.09338/) (2017)
- [Segmentation of Head and Neck Organs at Risk Using CNN with Batch Dice Loss](https://mlsanity.com/paper/1812.02427/) (2018)

## Built on by (most cited first, 1 of 1)

- [Modality-AGnostic Image Cascade (MAGIC) for Multi-Modality Cardiac Substructure Segmentation](https://mlsanity.com/paper/2506.10797/) (2025)

## Abstract (arXiv)

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.