The first validated open benchmark for future liver remnant segmentation is created from 197 refined CT volumes, with a cascaded nnU-Net achieving the highest Dice score of 0.767.
nnu-net: a self- configuring method for deep learning-based biomedical image segmentation,
4 Pith papers cite this work. Polarity classification is still indexing.
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CC-DiceCE boosts recall for small lesion segmentation in MRI with minimal degradation in other metrics and generally outperforms blob loss across datasets.
Structure augmentation via segmentation prior plus temporal aggregation stabilizes keyframe detection of fetal abdomen planes in blind-sweep ultrasound.
Hybrid U-Mamba architecture with Heat Conduction Operators achieves DSC of 0.8719 on Abdomen CT dataset by simulating frequency-domain thermal diffusion.
citing papers explorer
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Benchmarking Deep Learning for Future Liver Remnant Segmentation in Colorectal Liver Metastasis
The first validated open benchmark for future liver remnant segmentation is created from 197 refined CT volumes, with a cascaded nnU-Net achieving the highest Dice score of 0.767.
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Learning to Look Closer: A New Instance-Wise Loss for Small Cerebral Lesion Segmentation
CC-DiceCE boosts recall for small lesion segmentation in MRI with minimal degradation in other metrics and generally outperforms blob loss across datasets.
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Structure-Augmented Standard Plane Detection with Temporal Aggregation in Blind-Sweep Fetal Ultrasound
Structure augmentation via segmentation prior plus temporal aggregation stabilizes keyframe detection of fetal abdomen planes in blind-sweep ultrasound.
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Enhancing Medical Image Segmentation via Heat Conduction Equation
Hybrid U-Mamba architecture with Heat Conduction Operators achieves DSC of 0.8719 on Abdomen CT dataset by simulating frequency-domain thermal diffusion.