Pyramid Prediction Network for Semi-Supervised Segmentation Uncertainty Estimation based on Multi-Scale Discrepancy Uncertainty Rectifying Result Code Reference 本文提出了一种简单而高效的一致性正则化方法用于半监督医学图像分割,称为不确定性纠正金字塔一致性(URPC)。 Method 本文采用的网络结构如上图所示(Pyramid...
Lazarova, G.: "Semi-Supervised Image Segmentation". The 16th International Conference on Artificial Intelligence: Methodology, Systems, Applications, 2014Gergana Angelova Lazarova, "Semi-supervised image segmentation," in AIMSA, pp. 59-68. Springer, 2014....
Result: code: https://github.com/HiLab-git/DTCgithub.com/HiLab-git/DTC 参考文献: [1] Semi-supervised Medical Image Segmentation through Dual-task Consistency
Semi-Supervised Semantic Segmentation101 papers with code • 45 benchmarks • 13 datasets Models that are trained with a small number of labeled examples and a large number of unlabeled examples and whose aim is to learn to segment an image (i.e. assign a class to every pixel)....
Acquiring pixel-level annotations for histological image segmentation is time- and labor- consuming. Semi-supervised learning enables learning from the unlabeled and limited amount of labeled data. A challenging issue is the inconsistent and uncertain pr
Deep learning-based semi-supervised learning (SSL) algorithms have led to promising results in medical images segmentation and can alleviate doctors' expensive annotations by leveraging unlabeled data. However, most of the existing SSL algorithms in literature tend to regularize the model training by ...
4 Semi-Supervised Training with Adversarial Network 4.1 Network Architecture Segmentation network:使用带有ResNet-101的DeeLab-v2模型,模型在ImageNet数据集和MSCOCO数据集中进行预训练。去掉了多尺度融合,去掉最后一个分类层,将最后两个卷积层的stride从2变为1,输出的特征图分辨率为原图大小的1/8,为了扩大感受野,...
code 创新点: 利用两个分支结构分别处理low-level和high-level的特征,进行半监督语义分割 网络结构 上分支:Semi-Supervised Semantic Segmentation GAN (s4GAN) 下分支:Multi-Label Mean Teacher (MLMT) s4GAN 训练segmentation networkSS segmentation networkSS的损失函数由以下三部分组成: ...
cd code python train_LA_semisam_mt.py Test the model python test_LA.py 📚 Citation If you find this paper useful, please consider citing: @inproceedings{SemiSAM, title={SemiSAM: Enhancing Semi-Supervised Medical Image Segmentation via SAM-Assisted Consistency Regularization}, author={Zhang, Yi...
2024.1.18Semi-Supervised Medical Image Segmentation With Voxel Stability and Reliability Constraints 一、摘要 现有的师生模型严重受限于指数移动平均算法,从而陷入优化陷阱。此外,经典的不确定性估计方法计算的是图像的全局不确定性,但没有考虑局部区域级的不确定性,不适合区域模糊的医学图像。