Semi-supervised Medical Image Segmentation

35 papers with code • 2 benchmarks • 2 datasets

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Use these libraries to find Semi-supervised Medical Image Segmentation models and implementations
10 papers

Most implemented papers

Mutual Consistency Learning for Semi-supervised Medical Image Segmentation

HiLab-git/SSL4MIS 21 Sep 2021

In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation.

MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations with Limited Labels

moucheng2017/mismatchssl 23 Oct 2021

The state-of-the-art SSL methods in image classification utilise consistency regularisation to learn unlabelled predictions which are invariant to input level perturbations.

Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation

HiLab-git/SSL4MIS 2 Mar 2022

The pixel-level smoothness forces the model to generate invariant results under adversarial perturbations.

When CNN Meet with ViT: Towards Semi-Supervised Learning for Multi-Class Medical Image Semantic Segmentation

HiLab-git/SSL4MIS 12 Aug 2022

A topological exploration of all alternative supervision modes with CNN and ViT are detailed validated, demonstrating the most promising performance and specific setting of our method on semi-supervised medical image segmentation tasks.

Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation

HiLab-git/SSL4MIS 24 Mar 2023

Semi-supervised medical image segmentation has attracted much attention in recent years because of the high cost of medical image annotations.

ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast

HiLab-git/SSL4MIS 5 Apr 2023

In this work, we present ACTION++, an improved contrastive learning framework with adaptive anatomical contrast for semi-supervised medical segmentation.

Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentation

HiLab-git/SSL4MIS CVPR 2023

In semi-supervised medical image segmentation, there exist empirical mismatch problems between labeled and unlabeled data distribution.

A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation

ruizhe-l/semi-segmentation 16 Apr 2020

To address this problem, we propose a generic semi-supervised learning framework for image segmentation based on a deep convolutional neural network (DCNN).

Semi-supervised Medical Image Segmentation through Dual-task Consistency

HiLab-git/DTC 9 Sep 2020

Concretely, we use a dual-task deep network that jointly predicts a pixel-wise segmentation map and a geometry-aware level set representation of the target.

A Teacher-Student Framework for Semi-supervised Medical Image Segmentation From Mixed Supervision

Gollini/NSCLC_Radiogenomics 23 Oct 2020

We further proposed a localization branch realized via an aggregation of high-level features in a deep decoder to predict locations of organ and lesion, which enriches student segmentor with precise localization information.