BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

419 related articles for article (PubMed ID: 34766623)

  • 1. 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]  

  • 2. 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]  

  • 3. DAU-Net: Dual attention-aided U-Net for segmenting tumor in breast ultrasound images.
    Pramanik P; Roy A; Cuevas E; Perez-Cisneros M; Sarkar R
    PLoS One; 2024; 19(5):e0303670. PubMed ID: 38820462
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Improved breast ultrasound tumor classification using dual-input CNN with GAP-guided attention loss.
    Zou X; Zhai J; Qian S; Li A; Tian F; Cao X; Wang R
    Math Biosci Eng; 2023 Jul; 20(8):15244-15264. PubMed ID: 37679179
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Using BI-RADS Stratifications as Auxiliary Information for Breast Masses Classification in Ultrasound Images.
    Xing J; Chen C; Lu Q; Cai X; Yu A; Xu Y; Xia X; Sun Y; Xiao J; Huang L
    IEEE J Biomed Health Inform; 2021 Jun; 25(6):2058-2070. PubMed ID: 33119515
    [TBL] [Abstract][Full Text] [Related]  

  • 6. CTG-Net: Cross-task guided network for breast ultrasound diagnosis.
    Yang K; Suzuki A; Ye J; Nosato H; Izumori A; Sakanashi H
    PLoS One; 2022; 17(8):e0271106. PubMed ID: 35951606
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. CAM-QUS guided self-tuning modular CNNs with multi-loss functions for fully automated breast lesion classification in ultrasound images.
    Tasnim J; Hasan MK
    Phys Med Biol; 2023 Dec; 69(1):. PubMed ID: 38056017
    [No Abstract]   [Full Text] [Related]  

  • 9. 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]  

  • 10. Classification of multi-feature fusion ultrasound images of breast tumor within category 4 using convolutional neural networks.
    Xu P; Zhao J; Wan M; Song Q; Su Q; Wang D
    Med Phys; 2024 Jun; 51(6):4243-4257. PubMed ID: 38436433
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images.
    Ma H; Tian R; Li H; Sun H; Lu G; Liu R; Wang Z
    Biomed Eng Online; 2021 Nov; 20(1):112. PubMed ID: 34794443
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Two-stage CNNs for computerized BI-RADS categorization in breast ultrasound images.
    Huang Y; Han L; Dou H; Luo H; Yuan Z; Liu Q; Zhang J; Yin G
    Biomed Eng Online; 2019 Jan; 18(1):8. PubMed ID: 30678680
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. 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]  

  • 16. Channel Attention Module With Multiscale Grid Average Pooling for Breast Cancer Segmentation in an Ultrasound Image.
    Lee H; Park J; Hwang JY
    IEEE Trans Ultrason Ferroelectr Freq Control; 2020 Jul; 67(7):1344-1353. PubMed ID: 32054578
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A VGG attention vision transformer network for benign and malignant classification of breast ultrasound images.
    Qu X; Lu H; Tang W; Wang S; Zheng D; Hou Y; Jiang J
    Med Phys; 2022 Sep; 49(9):5787-5798. PubMed ID: 35866492
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Deep Learning Networks for Breast Lesion Classification in Ultrasound Images: A Comparative Study.
    Ferreira MR; Torres HR; Oliveira B; de Araujo ARVF; Morais P; Novais P; Vilaca JL
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083151
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 21.