2020年3月16日 · We introduce a novel similarity measure termed centerlineDice (short clDice), which is calculated on the intersection of the segmentation masks and their (morphological) …

2023年6月18日 · 本文介绍了一种新的用于管状结构分割的拓扑保持相似性度量cl-Dice。 本文提供了一个理论保证，即clDice同伦等价证明。 接下来，在损失函数中使用clDice的可微版本，即 …

Extending this, we propose a computationally efficient, differentiable loss function (soft-clDice) for training arbitrary neural segmentation networks. We benchmark the soft-clDice loss on five …

2023年2月9日 · 文章提出clDice函数，用于衡量管状网络结构如血管、道路的语义分割掩膜与其拓扑骨架的重合度，确保了拓扑关系的保留。 基于此，作者设计了一个高效的、可微分的soft …

提供了软-clDice作为训练神经网络的高效可微分损失函数，提升分割结果的连通性和体积分数。 此开源项目包含适用于PyTorch和TensorFlow/Keras的2D/3D实现，以及不同的平滑骨架方法。 …

The connectedness of the segmented vessels is often the most significant property for many applications such as disease modeling for neurodegeneration and stroke. We introduce a …

Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, the.

The connectedness of the segmented vessels is often the most significant property for many applications such as disease mo``deling for neurodegeneration and stroke. We introduce a …

We introduce a novel similarity measure termed center-lineDice (short clDice), which is calculated on the inter-section of the segmentation masks and their (morpholog-ical) skeleta. We …

2024年8月11日 · Centerline-Dice (cl-Dice)是一个将传统的Dice系数损失与分割结构的骨架或中心线相结合的度量。 这里的术语“骨架 skeleton”是指代表管状结构的中心路径或连接性的一像素 …