Výsledky vyhledávání - Semi-supervised learning 3D medical image segmentation Class imbalance Data augmentation

Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image Segmentation Autor Gu, Yuliang, Liu, Yepeng, Sun, Zhichao, Zhu, Jinchi, Xu, Yongchao, Najman, Laurent

“…Annotating 3D medical images demands expert knowledge and is time-consuming. As a result, semi-supervised learning (SSL…”
Získat plný text

When CNN Meet with ViT: Towards Semi-Supervised Learning for Multi-Class Medical Image Semantic Segmentation Autor Wang, Ziyang, Li, Tianze, Jian-Qing Zheng, Huang, Baoru

“…Due to the lack of quality annotation in medical imaging community, semi-supervised learning methods are highly valued in image semantic segmentation tasks…”
Získat plný text

Consistency learning with dynamic weighting and class-agnostic regularization for semi-supervised medical image segmentation Autor Su, Jiawei, Luo, Zhiming, Lian, Sheng, Lin, Dazhen, Li, Shaozi

“…Recently, significant progress has been made in consistency regularization-based semi-supervised medical image segmentation…”
Získat plný text

Semi-Supervised Volumetric Medical Image Segmentation via Class Prototype Guided Distribution-Aligned Representation Learning Autor Kong, Xiangyu, Ren, Zeyu, Liu, Lu

“…We present SemiCRL, a novel framework for volumetric medical image segmentation that formulates an innovative contrastive learning methodology in a semi-supervised learning setting…”
Získat plný text

Semi-Supervised Learning for Medical Image Segmentation Autor Li, Ruizhe

“…Medical image segmentation is a fundamental step in many computer aided clinical applications, such as tumour detection and quantification, organ measurement and feature learning, etc…”
Získat plný text

Entropy‐guided contrastive learning for semi‐supervised medical image segmentation Autor Xie, Junsong, Wu, Qian, Zhu, Renju

“…‐consuming and difficult to obtain. As a result, semi‐supervised learning (SSL) has gained attention as it has the potential to alleviate this challenge by using not only limited labelled data but also a large amount of unlabelled data…”
Získat plný text

Semi‐supervised medical image segmentation network based on mutual learning Autor Sun, Junmei, Wang, Tianyang, Wang, Meixi, Li, Xiumei, Xu, Yingying

“…Background Semi‐supervised learning provides an effective means to address the challenge of insufficient labeled data in medical image segmentation tasks…”
Získat plný text

Multidimensional perturbed consistency learning for semi‐supervised medical image segmentation Autor Yuan, Enze, Zhao, Bin, Qin, Xiao, Ding, Shuxue

“…) for more accurate semi‐supervised medical image segmentation. Specifically, we develop a multidimensional perturbation by considering the noise itself, the target object and the overall spatial architecture…”
Získat plný text

Dual Diversity and Pseudo‐Label Correction Learning for Semi‐Supervised Medical Image Segmentation Autor Du, Guangxing, Wu, Rui, Xu, Jinming, Zeng, Xiang, Xiong, Shengwu

“…ABSTRACT Semi‐supervised medical image segmentation has recently gained increasing research attention as it can reduce the need for large…”
Získat plný text

Dual‐Region Consistency Learning With Contrastive Refinement for Semi‐Supervised Medical Image Segmentation Autor Sun, Junmei, Wang, Meixi, Zhao, Jianxiang, Yang, Defu, Bai, Huang, Li, Xiumei

“… To address these issues, this paper proposes a novel semi‐supervised medical image segmentation framework named Dual…”
Získat plný text

FUSION: Uncertainty‐Guided Federated Semi‐Supervised Learning for Medical Image Segmentation Autor Raheem, Abdul, Yang, Zhen, Yu, Haiyang, Manan, Malik Abdul, Sabah, Fahad, Ahmed, Shahzad

“…Federated learning (FL) for medical image segmentation poses critical challenges, including non…”
Získat plný text

Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation Autor You, Chenyu, Zhao, Ruihan, Staib, Lawrence, Duncan, James S

“…Contrastive learning (CL) aims to learn useful representation without relying on expert annotations in the context of medical image segmentation…”
Zjistit podrobnosti o přístupu

Combining contrastive learning and shape awareness for semi-supervised medical image segmentation Autor Chen, Yaqi, Chen, Faquan, Huang, Chenxi

“… Semi-supervised segmentation (SSL) techniques make extensive use of unlabeled data to address the issue of the high acquisition cost of medically labeled data…”
Získat plný text

Rectified Mixed-Label Learning for Semi-Supervised Medical Image Segmentation Autor An, Zeyu, Chen, Zichong

“…Semi-supervised medical image segmentation (SSMIS) has gained increasing attention due to its potential to alleviate the manual annotation burden…”
Získat plný text

EPL: Evidential Prototype Learning for Semi-supervised Medical Image Segmentation Autor He, Yuanpeng

“…Although current semi-supervised medical segmentation methods can achieve decent performance, they are still affected by the uncertainty in unlabeled data and model predictions, and there is…”
Získat plný text

Learning Semi-Supervised Medical Image Segmentation from Spatial Registration Autor Liu, Qianying, Henderson, Paul, Gu, Xiao, Dai, Hang, Deligianni, Fani

“…Semi-supervised medical image segmentation has shown promise in training models with limited labeled data and abundant unlabeled data…”
Získat plný text

Model-Heterogeneous Semi-Supervised Federated Learning for Medical Image Segmentation Autor Ma, Yuxi, Wang, Jiacheng, Yang, Jing, Wang, Liansheng

“…Medical image segmentation is crucial in clinical diagnosis, helping physicians identify and analyze medical conditions…”
Získat plný text

Mixed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation Autor Li, Lijian

“…Recently, prototype learning has emerged in semi-supervised medical image segmentation and achieved remarkable performance…”
Získat plný text

Consistency and adversarial semi-supervised learning for medical image segmentation Autor Tang, Yongqiang, Wang, Shilei, Qu, Yuxun, Cui, Zhihua, Zhang, Wensheng

“… To settle above issue, in this paper, a novel semi-supervised medical image segmentation method is proposed, in which the adversarial training mechanism and the collaborative consistency learning…”
Získat plný text

Mutual Evidential Deep Learning for Semi-supervised Medical Image Segmentation Autor He, Yuanpeng, Bi, Yali, Li, Lijian, Pun, Chi-Man, Jiao, Wenpin, Jin, Zhi

“…Existing semi-supervised medical segmentation co-learning frameworks have realized that model performance can be diminished by the biases in model recognition caused by low-quality pseudo-labels…”
Získat plný text