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.
132 related articles for article (PubMed ID: 37695964)
1. Deep Semi-Supervised Ultrasound Image Segmentation by Using a Shadow Aware Network With Boundary Refinement. Chen F; Chen L; Kong W; Zhang W; Zheng P; Sun L; Zhang D; Liao H IEEE Trans Med Imaging; 2023 Dec; 42(12):3779-3793. PubMed ID: 37695964 [TBL] [Abstract][Full Text] [Related]
2. Shadow-Consistent Semi-Supervised Learning for Prostate Ultrasound Segmentation. Xu X; Sanford T; Turkbey B; Xu S; Wood BJ; Yan P IEEE Trans Med Imaging; 2022 Jun; 41(6):1331-1345. PubMed ID: 34971530 [TBL] [Abstract][Full Text] [Related]
3. Semi-supervised segmentation of lesion from breast ultrasound images with attentional generative adversarial network. Han L; Huang Y; Dou H; Wang S; Ahamad S; Luo H; Liu Q; Fan J; Zhang J Comput Methods Programs Biomed; 2020 Jun; 189():105275. PubMed ID: 31978805 [TBL] [Abstract][Full Text] [Related]
4. Bone shadow segmentation from ultrasound data for orthopedic surgery using GAN. Alsinan AZ; Patel VM; Hacihaliloglu I Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1477-1485. PubMed ID: 32656685 [TBL] [Abstract][Full Text] [Related]
5. 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]
7. Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation. Chaitanya K; Erdil E; Karani N; Konukoglu E Med Image Anal; 2023 Jul; 87():102792. PubMed ID: 37054649 [TBL] [Abstract][Full Text] [Related]
8. Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging. Meng Q; Sinclair M; Zimmer V; Hou B; Rajchl M; Toussaint N; Oktay O; Schlemper J; Gomez A; Housden J; Matthew J; Rueckert D; Schnabel JA; Kainz B IEEE Trans Med Imaging; 2019 Dec; 38(12):2755-2767. PubMed ID: 31021795 [TBL] [Abstract][Full Text] [Related]
9. A modality-collaborative convolution and transformer hybrid network for unpaired multi-modal medical image segmentation with limited annotations. Liu H; Zhuang Y; Song E; Xu X; Ma G; Cetinkaya C; Hung CC Med Phys; 2023 Sep; 50(9):5460-5478. PubMed ID: 36864700 [TBL] [Abstract][Full Text] [Related]
10. BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis. Zhang E; Seiler S; Chen M; Lu W; Gu X Phys Med Biol; 2020 Jun; 65(12):125005. PubMed ID: 32155605 [TBL] [Abstract][Full Text] [Related]
11. C-Net: Cascaded convolutional neural network with global guidance and refinement residuals for breast ultrasound images segmentation. Chen G; Dai Y; Zhang J Comput Methods Programs Biomed; 2022 Oct; 225():107086. PubMed ID: 36044802 [TBL] [Abstract][Full Text] [Related]
12. Boundary-oriented Network for Automatic Breast Tumor Segmentation in Ultrasound Images. Zhang M; Huang A; Yang D; Xu R Ultrason Imaging; 2023 Mar; 45(2):62-73. PubMed ID: 36951101 [TBL] [Abstract][Full Text] [Related]
13. SMU-Net: Saliency-Guided Morphology-Aware U-Net for Breast Lesion Segmentation in Ultrasound Image. Ning Z; Zhong S; Feng Q; Chen W; Zhang Y IEEE Trans Med Imaging; 2022 Feb; 41(2):476-490. PubMed ID: 34582349 [TBL] [Abstract][Full Text] [Related]
14. Uncertainty Aware Temporal-Ensembling Model for Semi-Supervised ABUS Mass Segmentation. Cao X; Chen H; Li Y; Peng Y; Wang S; Cheng L IEEE Trans Med Imaging; 2021 Jan; 40(1):431-443. PubMed ID: 33021936 [TBL] [Abstract][Full Text] [Related]
15. AAU-Net: An Adaptive Attention U-Net for Breast Lesions Segmentation in Ultrasound Images. Chen G; Li L; Dai Y; Zhang J; Yap MH IEEE Trans Med Imaging; 2023 May; 42(5):1289-1300. PubMed ID: 36455083 [TBL] [Abstract][Full Text] [Related]
16. A Robust Breast ultrasound segmentation method under noisy annotations. Zou H; Gong X; Luo J; Li T Comput Methods Programs Biomed; 2021 Sep; 209():106327. PubMed ID: 34428680 [TBL] [Abstract][Full Text] [Related]
17. Boundary-Guided and Region-Aware Network With Global Scale-Adaptive for Accurate Segmentation of Breast Tumors in Ultrasound Images. Hu K; Zhang X; Lee D; Xiong D; Zhang Y; Gao X IEEE J Biomed Health Inform; 2023 Sep; 27(9):4421-4432. PubMed ID: 37310830 [TBL] [Abstract][Full Text] [Related]
18. Sd-net: a semi-supervised double-cooperative network for liver segmentation from computed tomography (CT) images. Huang S; Luo J; Ou Y; Shen W; Pang Y; Nie X; Zhang G J Cancer Res Clin Oncol; 2024 Feb; 150(2):79. PubMed ID: 38316678 [TBL] [Abstract][Full Text] [Related]
19. BAG-Net: a boundary detection and multiple attention-guided network for liver ultrasound image automatic segmentation in ultrasound guided surgery. Ji Z; Che H; Yan Y; Wu J Phys Med Biol; 2024 Jan; 69(3):. PubMed ID: 38198733 [No Abstract] [Full Text] [Related]
20. Global guidance network for breast lesion segmentation in ultrasound images. Xue C; Zhu L; Fu H; Hu X; Li X; Zhang H; Heng PA Med Image Anal; 2021 May; 70():101989. PubMed ID: 33640719 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]