Medical Image Segmentation based on Deep Active Contour and Mean Curvature Loss Function

arXiv:2607.12586 · eess.IV, cs.CV · Submitted 2026-07-14 · Read on arXiv

eess.IV, cs.CV

Submitted: 2026-07-14

Updated: 2026-09-18

Project page: https://www.kaggle.com/datasets/zxcv2022/digital-medical-images-for--downloadresource

Terminology

• Loss Function — 51× in this paper · explained in 2 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Ablation — 4× in this paper · explained in 1 episode
• Deep Active Contour and Mean Curvature — 4× in this paper
• Interpretability — 3× in this paper · explained in 15 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Activation Function — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Average Surface Distance — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Dice Similarity Coefficient — 1× in this paper
• Dice-Coefficient Loss — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Jaccard Similarity — 1× in this paper
• Medical Image Computing and Computer-Assisted Intervention — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Recent Advances in Medical Imaging Segmentation: A Survey
• Topology-Preserving Image Segmentation with Spatial-Aware Persistent Feature Matching
• LMS-Net: A Learned Mumford-Shah Network For Few-Shot Medical Image Segmentation
• Learning Euler's Elastica Model for Medical Image Segmentation
• Active Contour Models Driven by Hyperbolic Mean Curvature Flow for Image Segmentation

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