Placenta Segmentation
5 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
Automatic 3D Multi-modal Ultrasound Segmentation of Human Placenta using Fusion Strategies and Deep Learning
Methods: We propose an automatic three-dimensional multi-modal (B-mode and power Doppler) ultrasound segmentation of the human placenta using deep learning combined with different fusion strategies. We collected data containing Bmode and power Doppler ultrasound scans for 400 studies.
PlaNet-S: Automatic Semantic Segmentation of Placenta
[Purpose] To develop a fully automated semantic placenta segmentation model that integrates the U-Net and SegNeXt architectures through ensemble learning.
Test-time augmentation-based active learning and self-training for label-efficient segmentation
However, while self-training improved the performance of single-sequence fetal body segmentation when combined with AL, it slightly deteriorated performance of multi-sequence placenta segmentation on ID data.
Contour Dice loss for structures with Fuzzy and Complex Boundaries in Fetal MRI
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.
