These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
550 related articles for article (PubMed ID: 30959445)
1. Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis. Cheplygina V; de Bruijne M; Pluim JPW Med Image Anal; 2019 May; 54():280-296. PubMed ID: 30959445 [TBL] [Abstract][Full Text] [Related]
2. Shifting to machine supervision: annotation-efficient semi and self-supervised learning for automatic medical image segmentation and classification. Singh P; Chukkapalli R; Chaudhari S; Chen L; Chen M; Pan J; Smuda C; Cirrone J Sci Rep; 2024 May; 14(1):10820. PubMed ID: 38734825 [TBL] [Abstract][Full Text] [Related]
3. Cyclic Learning: Bridging Image-Level Labels and Nuclei Instance Segmentation. Zhou Y; Wu Y; Wang Z; Wei B; Lai M; Shou J; Fan Y; Xu Y IEEE Trans Med Imaging; 2023 Oct; 42(10):3104-3116. PubMed ID: 37171933 [TBL] [Abstract][Full Text] [Related]
4. An Efficient Semi-Supervised Framework with Multi-Task and Curriculum Learning for Medical Image Segmentation. Wang K; Wang Y; Zhan B; Yang Y; Zu C; Wu X; Zhou J; Nie D; Zhou L Int J Neural Syst; 2022 Sep; 32(9):2250043. PubMed ID: 35912583 [TBL] [Abstract][Full Text] [Related]
5. MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology images. Sebai M; Wang X; Wang T Med Biol Eng Comput; 2020 Jul; 58(7):1603-1623. PubMed ID: 32445109 [TBL] [Abstract][Full Text] [Related]
6. Recent advances and clinical applications of deep learning in medical image analysis. Chen X; Wang X; Zhang K; Fung KM; Thai TC; Moore K; Mannel RS; Liu H; Zheng B; Qiu Y Med Image Anal; 2022 Jul; 79():102444. PubMed ID: 35472844 [TBL] [Abstract][Full Text] [Related]
7. Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency. Luo X; Wang G; Liao W; Chen J; Song T; Chen Y; Zhang S; Metaxas DN; Zhang S Med Image Anal; 2022 Aug; 80():102517. PubMed ID: 35732106 [TBL] [Abstract][Full Text] [Related]
8. Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images. Gao F; Hu M; Zhong ME; Feng S; Tian X; Meng X; Ni-Jia-Ti MY; Huang Z; Lv M; Song T; Zhang X; Zou X; Wu X Med Image Anal; 2022 Aug; 80():102515. PubMed ID: 35780593 [TBL] [Abstract][Full Text] [Related]
9. Linear semantic transformation for semi-supervised medical image segmentation. Chen C; Chen Y; Li X; Ning H; Xiao R Comput Biol Med; 2024 May; 173():108331. PubMed ID: 38522252 [TBL] [Abstract][Full Text] [Related]
10. Chronic gastritis classification using gastric X-ray images with a semi-supervised learning method based on tri-training. Li Z; Togo R; Ogawa T; Haseyama M Med Biol Eng Comput; 2020 Jun; 58(6):1239-1250. PubMed ID: 32221796 [TBL] [Abstract][Full Text] [Related]
11. PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation. Wang G; Luo X; Gu R; Yang S; Qu Y; Zhai S; Zhao Q; Li K; Zhang S Comput Methods Programs Biomed; 2023 Apr; 231():107398. PubMed ID: 36773591 [TBL] [Abstract][Full Text] [Related]
12. Constrained Deep Weak Supervision for Histopathology Image Segmentation. Jia Z; Huang X; Chang EI; Xu Y IEEE Trans Med Imaging; 2017 Nov; 36(11):2376-2388. PubMed ID: 28692971 [TBL] [Abstract][Full Text] [Related]
13. Weakly supervised learning for multi-class medical image segmentation via feature decomposition. Kuang Z; Yan Z; Yu L Comput Biol Med; 2024 Mar; 171():108228. PubMed ID: 38422964 [TBL] [Abstract][Full Text] [Related]
14. Learning with limited annotations: A survey on deep semi-supervised learning for medical image segmentation. Jiao R; Zhang Y; Ding L; Xue B; Zhang J; Cai R; Jin C Comput Biol Med; 2024 Feb; 169():107840. PubMed ID: 38157773 [TBL] [Abstract][Full Text] [Related]
15. Semi-supervised training using cooperative labeling of weakly annotated data for nodule detection in chest CT. Maynord M; Farhangi MM; Fermüller C; Aloimonos Y; Levine G; Petrick N; Sahiner B; Pezeshk A Med Phys; 2023 Jul; 50(7):4255-4268. PubMed ID: 36630691 [TBL] [Abstract][Full Text] [Related]
16. Constrained-CNN losses for weakly supervised segmentation. Kervadec H; Dolz J; Tang M; Granger E; Boykov Y; Ben Ayed I Med Image Anal; 2019 May; 54():88-99. PubMed ID: 30851541 [TBL] [Abstract][Full Text] [Related]
17. Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation. Curti N; Merli Y; Zengarini C; Giampieri E; Merlotti A; Dall'Olio D; Marcelli E; Bianchi T; Castellani G Int J Mol Sci; 2022 Dec; 24(1):. PubMed ID: 36614147 [TBL] [Abstract][Full Text] [Related]
18. Self-supervised pre-training with contrastive and masked autoencoder methods for dealing with small datasets in deep learning for medical imaging. Wolf D; Payer T; Lisson CS; Lisson CG; Beer M; Götz M; Ropinski T Sci Rep; 2023 Nov; 13(1):20260. PubMed ID: 37985685 [TBL] [Abstract][Full Text] [Related]
19. Semi-supervised task-driven data augmentation for medical image segmentation. Chaitanya K; Karani N; Baumgartner CF; Erdil E; Becker A; Donati O; Konukoglu E Med Image Anal; 2021 Feb; 68():101934. PubMed ID: 33385699 [TBL] [Abstract][Full Text] [Related]
20. Boundary sample-based class-weighted semi-supervised learning for malignant tumor classification of medical imaging. Fang P; Feng R; Liu C; Wen R Med Biol Eng Comput; 2024 Oct; 62(10):2987-2997. PubMed ID: 38727760 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]