Hierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation

05/21/2021
by   Shumeng Li, et al.
0

Deep learning has achieved promising segmentation performance on 3D left atrium MR images. However, annotations for segmentation tasks are expensive, costly and difficult to obtain. In this paper, we introduce a novel hierarchical consistency regularized mean teacher framework for 3D left atrium segmentation. In each iteration, the student model is optimized by multi-scale deep supervision and hierarchical consistency regularization, concurrently. Extensive experiments have shown that our method achieves competitive performance as compared with full annotation, outperforming other stateof-the-art semi-supervised segmentation methods.

READ FULL TEXT
research
07/16/2019

Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation

Training deep convolutional neural networks usually requires a large amo...
research
03/05/2022

Adversarial Dual-Student with Differentiable Spatial Warping for Semi-Supervised Semantic Segmentation

A common challenge posed to robust semantic segmentation is the expensiv...
research
10/20/2022

Cyclical Self-Supervision for Semi-Supervised Ejection Fraction Prediction from Echocardiogram Videos

Left-ventricular ejection fraction (LVEF) is an important indicator of h...
research
09/17/2021

Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data

Semi-supervised learning provides great significance in left atrium (LA)...
research
07/12/2018

Deep semi-supervised segmentation with weight-averaged consistency targets

Recently proposed techniques for semi-supervised learning such as Tempor...
research
03/04/2019

Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model

Automated brain lesion segmentation provides valuable information for th...
research
10/22/2021

Semi-Supervised Semantic Segmentation of Vessel Images using Leaking Perturbations

Semantic segmentation based on deep learning methods can attain appealin...

Please sign up or login with your details

Forgot password? Click here to reset