BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

186 related articles for article (PubMed ID: 34280097)

  • 1. Feature Pyramid Nonlocal Network With Transform Modal Ensemble Learning for Breast Tumor Segmentation in Ultrasound Images.
    Tang P; Yang X; Nan Y; Xiang S; Liang Q
    IEEE Trans Ultrason Ferroelectr Freq Control; 2021 Dec; 68(12):3549-3559. PubMed ID: 34280097
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. A neural network with a human learning paradigm for breast fibroadenoma segmentation in sonography.
    Guo Y; Chen M; Yang L; Yin H; Yang H; Zhou Y
    Biomed Eng Online; 2024 Jan; 23(1):5. PubMed ID: 38221632
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Breast ultrasound image segmentation: A coarse-to-fine fusion convolutional neural network.
    Wang K; Liang S; Zhong S; Feng Q; Ning Z; Zhang Y
    Med Phys; 2021 Aug; 48(8):4262-4278. PubMed ID: 34053092
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An attention-supervised full-resolution residual network for the segmentation of breast ultrasound images.
    Qu X; Shi Y; Hou Y; Jiang J
    Med Phys; 2020 Nov; 47(11):5702-5714. PubMed ID: 32964449
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.
    Hu Y; Guo Y; Wang Y; Yu J; Li J; Zhou S; Chang C
    Med Phys; 2019 Jan; 46(1):215-228. PubMed ID: 30374980
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Cross-Model Attention-Guided Tumor Segmentation for 3D Automated Breast Ultrasound (ABUS) Images.
    Zhou Y; Chen H; Li Y; Cao X; Wang S; Shen D
    IEEE J Biomed Health Inform; 2022 Jan; 26(1):301-311. PubMed ID: 34003755
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accurate segmentation of breast tumor in ultrasound images through joint training and refined segmentation.
    Shen X; Wu X; Liu R; Li H; Yin J; Wang L; Ma H
    Phys Med Biol; 2022 Sep; 67(17):. PubMed ID: 35961304
    [No Abstract]   [Full Text] [Related]  

  • 9. Multiscale superpixel method for segmentation of breast ultrasound.
    Ilesanmi AE; Idowu OP; Makhanov SS
    Comput Biol Med; 2020 Oct; 125():103879. PubMed ID: 32890977
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A hybrid attentional guidance network for tumors segmentation of breast ultrasound images.
    Lu Y; Jiang X; Zhou M; Zhi D; Qiu R; Ou Z; Bai J
    Int J Comput Assist Radiol Surg; 2023 Aug; 18(8):1489-1500. PubMed ID: 36853584
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. BUS-Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets.
    Thomas C; Byra M; Marti R; Yap MH; Zwiggelaar R
    Med Phys; 2023 May; 50(5):3223-3243. PubMed ID: 36794706
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Discriminative Level Set Method with Deep Supervision for Breast Tumor Segmentation.
    Hussain S; Xi X; Ullah I; Inam SA; Naz F; Shaheed K; Ali SA; Tian C
    Comput Biol Med; 2022 Oct; 149():105995. PubMed ID: 36055157
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. 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]  

  • 16. Automatic breast ultrasound (ABUS) tumor segmentation based on global and local feature fusion.
    Li Y; Ren Y; Cheng Z; Sun J; Pan P; Chen H
    Phys Med Biol; 2024 May; 69(11):. PubMed ID: 38759673
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Dilated densely connected U-Net with uncertainty focus loss for 3D ABUS mass segmentation.
    Cao X; Chen H; Li Y; Peng Y; Wang S; Cheng L
    Comput Methods Programs Biomed; 2021 Sep; 209():106313. PubMed ID: 34364182
    [TBL] [Abstract][Full Text] [Related]  

  • 19. FMRNet: A fused network of multiple tumoral regions for breast tumor classification with ultrasound images.
    Cui W; Peng Y; Yuan G; Cao W; Cao Y; Lu Z; Ni X; Yan Z; Zheng J
    Med Phys; 2022 Jan; 49(1):144-157. PubMed ID: 34766623
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images.
    Zhou Y; Chen H; Li Y; Liu Q; Xu X; Wang S; Yap PT; Shen D
    Med Image Anal; 2021 May; 70():101918. PubMed ID: 33676100
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.