183 related articles for article (PubMed ID: 37190469)
1. Semi-Supervised Semantic Segmentation of Remote Sensing Images Based on Dual Cross-Entropy Consistency.
Cui M; Li K; Li Y; Kamuhanda D; Tessone CJ
Entropy (Basel); 2023 Apr; 25(4):. PubMed ID: 37190469
[TBL] [Abstract][Full Text] [Related]
2. Efficient Combination of CNN and Transformer for Dual-Teacher Uncertainty-guided Semi-supervised Medical Image Segmentation.
Xiao Z; Su Y; Deng Z; Zhang W
Comput Methods Programs Biomed; 2022 Nov; 226():107099. PubMed ID: 36116398
[TBL] [Abstract][Full Text] [Related]
3. Enhancing Semi-Supervised Semantic Segmentation of Remote Sensing Images via Feature Perturbation-Based Consistency Regularization Methods.
Xin Y; Fan Z; Qi X; Geng Y; Li X
Sensors (Basel); 2024 Jan; 24(3):. PubMed ID: 38339447
[TBL] [Abstract][Full Text] [Related]
4. MDT: semi-supervised medical image segmentation with mixup-decoupling training.
Long J; Ren Y; Yang C; Ren P; Zeng Z
Phys Med Biol; 2024 Mar; 69(6):. PubMed ID: 38324897
[No Abstract] [Full Text] [Related]
5. Querying Labeled for Unlabeled: Cross-Image Semantic Consistency Guided Semi-Supervised Semantic Segmentation.
Wu L; Fang L; He X; He M; Ma J; Zhong Z
IEEE Trans Pattern Anal Mach Intell; 2023 Jul; 45(7):8827-8844. PubMed ID: 37018311
[TBL] [Abstract][Full Text] [Related]
6. Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.
Liu B; Desrosiers C; Ben Ayed I; Dolz J
Med Image Anal; 2023 Jan; 83():102670. PubMed ID: 36413905
[TBL] [Abstract][Full Text] [Related]
7. Correspondence-based Generative Bayesian Deep Learning for semi-supervised volumetric medical image segmentation.
Zhao Y; Zhou X; Pan T; Gao S; Zhang W
Comput Med Imaging Graph; 2024 Apr; 113():102352. PubMed ID: 38341947
[TBL] [Abstract][Full Text] [Related]
8. Semi-TMS: an efficient regularization-oriented triple-teacher semi-supervised medical image segmentation model.
Chen W; Zhou S; Liu X; Chen Y
Phys Med Biol; 2023 Oct; 68(20):. PubMed ID: 37699409
[No Abstract] [Full Text] [Related]
9. Feature-enhanced adversarial semi-supervised semantic segmentation network for pulmonary embolism annotation.
Cheng TW; Chua YW; Huang CC; Chang J; Kuo C; Cheng YC
Heliyon; 2023 May; 9(5):e16060. PubMed ID: 37215788
[TBL] [Abstract][Full Text] [Related]
10. STAMP: A Self-training Student-Teacher Augmentation-Driven Meta Pseudo-Labeling Framework for 3D Cardiac MRI Image Segmentation.
Hasan SMK; Linte C
Med Image Underst Anal (2022); 2022; 13413():371-386. PubMed ID: 37126464
[TBL] [Abstract][Full Text] [Related]
11. Boundary attention with multi-task consistency constraints for semi-supervised 2D echocardiography segmentation.
Zhao Y; Liao K; Zheng Y; Zhou X; Guo X
Comput Biol Med; 2024 Mar; 171():108100. PubMed ID: 38340441
[TBL] [Abstract][Full Text] [Related]
12. Real-time coronary artery segmentation in CAG images: A semi-supervised deep learning strategy.
Lee CK; Hong JW; Wu CL; Hou JM; Lin YA; Huang KC; Tseng PH
Artif Intell Med; 2024 Jul; 153():102888. PubMed ID: 38781870
[TBL] [Abstract][Full Text] [Related]
13. A regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation.
Wang Q; Li X; Chen M; Chen L; Chen J
Phys Med Biol; 2022 Aug; 67(17):. PubMed ID: 35970179
[No Abstract] [Full Text] [Related]
14. Semantic contrast with uncertainty-aware pseudo label for lumbar semi-supervised classification.
Hai J; Chen J; Qiao K; Liang N; Su Z; Lv H; Yan B
Comput Biol Med; 2024 Jun; 178():108754. PubMed ID: 38878404
[TBL] [Abstract][Full Text] [Related]
15. Semi-supervised medical image segmentation via feature similarity and reliable-region enhancement.
Long J; Yang C; Ren Y; Zeng Z
Comput Biol Med; 2023 Dec; 167():107668. PubMed ID: 37931524
[TBL] [Abstract][Full Text] [Related]
16. RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation.
Zhao X; Qi Z; Wang S; Wang Q; Wu X; Mao Y; Zhang L
IEEE J Biomed Health Inform; 2023 Oct; PP():. PubMed ID: 37801388
[TBL] [Abstract][Full Text] [Related]
17. All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-Supervised Medical Image Segmentation.
Xu Z; Wang Y; Lu D; Yu L; Yan J; Luo J; Ma K; Zheng Y; Tong RK
IEEE J Biomed Health Inform; 2022 Jul; 26(7):3174-3184. PubMed ID: 35324450
[TBL] [Abstract][Full Text] [Related]
18. Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning.
Wang K; Zhan B; Zu C; Wu X; Zhou J; Zhou L; Wang Y
Med Image Anal; 2022 Jul; 79():102447. PubMed ID: 35509136
[TBL] [Abstract][Full Text] [Related]
19. The student-teacher framework guided by self-training and consistency regularization for semi-supervised medical image segmentation.
Li B; Xu Y; Wang Y; Li L; Zhang B
PLoS One; 2024; 19(4):e0300039. PubMed ID: 38648206
[TBL] [Abstract][Full Text] [Related]
20. MUE-CoT: multi-scale uncertainty entropy-aware co-training framework for left atrial segmentation.
Hao D; Li H; Zhang Y; Zhang Q
Phys Med Biol; 2023 Oct; 68(21):. PubMed ID: 37567214
[No Abstract] [Full Text] [Related]
[Next] [New Search]
