Pseudo-label refinement using superpixels for semi-supervised brain tumour segmentation
Fuente:
arXiv
Saved in:
| Main Authors: | Thompson, Bethany H., Di Caterina, Gaetano, Voisey, Jeremy P. |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Better (pseudo-)labels for semi-supervised instance segmentation
by: Porcher, François, et al.
Published: (2024)
by: Porcher, François, et al.
Published: (2024)
Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation
by: Jin, Qiangguo, et al.
Published: (2025)
by: Jin, Qiangguo, et al.
Published: (2025)
ERSR: An Ellipse-constrained pseudo-label refinement and symmetric regularization framework for semi-supervised fetal head segmentation in ultrasound images
by: Zhou, Linkuan, et al.
Published: (2025)
by: Zhou, Linkuan, et al.
Published: (2025)
Superpixel Anything: A general object-based framework for accurate yet regular superpixel segmentation
by: Walther, Julien, et al.
Published: (2025)
by: Walther, Julien, et al.
Published: (2025)
Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification
by: Chatterjee, Soumick, et al.
Published: (2022)
by: Chatterjee, Soumick, et al.
Published: (2022)
SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation
by: Yin, Jun, et al.
Published: (2025)
by: Yin, Jun, et al.
Published: (2025)
Robust superpixels using color and contour features along linear path
by: Giraud, Rémi, et al.
Published: (2019)
by: Giraud, Rémi, et al.
Published: (2019)
INSITE: labelling medical images using submodular functions and semi-supervised data programming
by: Gautam, Akshat, et al.
Published: (2024)
by: Gautam, Akshat, et al.
Published: (2024)
SP${ }^3$ : Superpixel-propagated pseudo-label learning for weakly semi-supervised medical image segmentation
by: Li, Shiman, et al.
Published: (2024)
by: Li, Shiman, et al.
Published: (2024)
BoundMatch: Boundary detection applied to semi-supervised segmentation
by: Ishikawa, Haruya, et al.
Published: (2025)
by: Ishikawa, Haruya, et al.
Published: (2025)
A comprehensive review and new taxonomy on superpixel segmentation
by: Barcelos, I. B., et al.
Published: (2024)
by: Barcelos, I. B., et al.
Published: (2024)
Cross-pyramid consistency regularization for semi-supervised medical image segmentation
by: Bojko, Matus, et al.
Published: (2025)
by: Bojko, Matus, et al.
Published: (2025)
RePL: Pseudo-label Refinement for Semi-supervised LiDAR Semantic Segmentation
by: Kwon, Donghyeon, et al.
Published: (2026)
by: Kwon, Donghyeon, et al.
Published: (2026)
Cross-head mutual Mean-Teaching for semi-supervised medical image segmentation
by: Li, Wei, et al.
Published: (2023)
by: Li, Wei, et al.
Published: (2023)
Enhancing efficiency in paediatric brain tumour segmentation using a pathologically diverse single-center clinical dataset
by: Piffer, A., et al.
Published: (2025)
by: Piffer, A., et al.
Published: (2025)
UCAD: Uncertainty-guided Contour-aware Displacement for semi-supervised medical image segmentation
by: Ding, Chengbo, et al.
Published: (2026)
by: Ding, Chengbo, et al.
Published: (2026)
Self Adaptive Threshold Pseudo-labeling and Unreliable Sample Contrastive Loss for Semi-supervised Image Classification
by: Zhang, Xuerong, et al.
Published: (2024)
by: Zhang, Xuerong, et al.
Published: (2024)
Robust Noisy Pseudo-label Learning for Semi-supervised Medical Image Segmentation Using Diffusion Model
by: Xi, Lin, et al.
Published: (2025)
by: Xi, Lin, et al.
Published: (2025)
Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation
by: Jin, Qiangguo, et al.
Published: (2024)
by: Jin, Qiangguo, et al.
Published: (2024)
A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms
by: Blau, Ari, et al.
Published: (2024)
by: Blau, Ari, et al.
Published: (2024)
NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training
by: Luginov, Albert, et al.
Published: (2024)
by: Luginov, Albert, et al.
Published: (2024)
Leveraging Fixed and Dynamic Pseudo-labels for Semi-supervised Medical Image Segmentation
by: Kumari, Suruchi, et al.
Published: (2024)
by: Kumari, Suruchi, et al.
Published: (2024)
SegMatch: A semi-supervised learning method for surgical instrument segmentation
by: Wei, Meng, et al.
Published: (2023)
by: Wei, Meng, et al.
Published: (2023)
OXSeg: Multidimensional attention UNet-based lip segmentation using semi-supervised lip contours
by: Moghaddasi, Hanie, et al.
Published: (2025)
by: Moghaddasi, Hanie, et al.
Published: (2025)
Uncertainty-aware Long-tailed Weights Model the Utility of Pseudo-labels for Semi-supervised Learning
by: Wu, Jiaqi, et al.
Published: (2025)
by: Wu, Jiaqi, et al.
Published: (2025)
STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation
by: Wang, Yaqi, et al.
Published: (2024)
by: Wang, Yaqi, et al.
Published: (2024)
Soft labelling for semantic segmentation: Bringing coherence to label down-sampling
by: Alcover-Couso, Roberto, et al.
Published: (2023)
by: Alcover-Couso, Roberto, et al.
Published: (2023)
Learning to segment anatomy and lesions from disparately labeled sources in brain MRI
by: Himmetoglu, Meva, et al.
Published: (2025)
by: Himmetoglu, Meva, et al.
Published: (2025)
A Channel-ensemble Approach: Unbiased and Low-variance Pseudo-labels is Critical for Semi-supervised Classification
by: Wu, Jiaqi, et al.
Published: (2024)
by: Wu, Jiaqi, et al.
Published: (2024)
MetaSSP: Enhancing Semi-supervised Implicit 3D Reconstruction through Meta-adaptive EMA and SDF-aware Pseudo-label Evaluation
by: Zhang, Luoxi, et al.
Published: (2026)
by: Zhang, Luoxi, et al.
Published: (2026)
Label-supervised surgical instrument segmentation using temporal equivariance and semantic continuity
by: Wang, Qiyuan, et al.
Published: (2024)
by: Wang, Qiyuan, et al.
Published: (2024)
Pseudo-labeling with Keyword Refining for Few-Supervised Video Captioning
by: Li, Ping, et al.
Published: (2024)
by: Li, Ping, et al.
Published: (2024)
Confident Pseudo-labeled Diffusion Augmentation for Canine Cardiomegaly Detection
by: Zhang, Shiman, et al.
Published: (2025)
by: Zhang, Shiman, et al.
Published: (2025)
Boosting Box-supervised Instance Segmentation with Pseudo Depth
by: Yu, Xinyi, et al.
Published: (2024)
by: Yu, Xinyi, et al.
Published: (2024)
More Reliable Pseudo-labels, Better Performance: A Generalized Approach to Single Positive Multi-label Learning
by: Tran, Luong, et al.
Published: (2025)
by: Tran, Luong, et al.
Published: (2025)
FLAIRBrainSeg: Fine-grained brain segmentation using FLAIR MRI only
by: Bot, Edern Le, et al.
Published: (2025)
by: Bot, Edern Le, et al.
Published: (2025)
Attribute Guidance With Inherent Pseudo-label For Occluded Person Re-identification
by: Zhi, Rui, et al.
Published: (2025)
by: Zhi, Rui, et al.
Published: (2025)
Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model
by: Toba, Masahito, et al.
Published: (2024)
by: Toba, Masahito, et al.
Published: (2024)
Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization
by: Khan, Adnan, et al.
Published: (2024)
by: Khan, Adnan, et al.
Published: (2024)
Multi-task learning on partially labeled datasets via invariant/equivariant semi-supervised learning
by: Rabadán, Miquel Martí i, et al.
Published: (2026)
by: Rabadán, Miquel Martí i, et al.
Published: (2026)
Similar Items
-
Better (pseudo-)labels for semi-supervised instance segmentation
by: Porcher, François, et al.
Published: (2024) -
Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation
by: Jin, Qiangguo, et al.
Published: (2025) -
ERSR: An Ellipse-constrained pseudo-label refinement and symmetric regularization framework for semi-supervised fetal head segmentation in ultrasound images
by: Zhou, Linkuan, et al.
Published: (2025) -
Superpixel Anything: A general object-based framework for accurate yet regular superpixel segmentation
by: Walther, Julien, et al.
Published: (2025) -
Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification
by: Chatterjee, Soumick, et al.
Published: (2022)