BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1039 related articles for article (PubMed ID: 30346279)

  • 1. Ultrasound Image Segmentation: A Deeply Supervised Network With Attention to Boundaries.
    Mishra D; Chaudhury S; Sarkar M; Soin AS
    IEEE Trans Biomed Eng; 2019 Jun; 66(6):1637-1648. PubMed ID: 30346279
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
    Tong N; Gou S; Yang S; Ruan D; Sheng K
    Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep morphology aided diagnosis network for segmentation of carotid artery vessel wall and diagnosis of carotid atherosclerosis on black-blood vessel wall MRI.
    Wu J; Xin J; Yang X; Sun J; Xu D; Zheng N; Yuan C
    Med Phys; 2019 Dec; 46(12):5544-5561. PubMed ID: 31356693
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deeply self-supervised contour embedded neural network applied to liver segmentation.
    Chung M; Lee J; Lee M; Lee J; Shin YG
    Comput Methods Programs Biomed; 2020 Aug; 192():105447. PubMed ID: 32203792
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Automatic liver segmentation by integrating fully convolutional networks into active contour models.
    Guo X; Schwartz LH; Zhao B
    Med Phys; 2019 Oct; 46(10):4455-4469. PubMed ID: 31356688
    [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. 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]  

  • 8. Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
    Burton W; Myers C; Rullkoetter P
    Comput Methods Programs Biomed; 2020 Jun; 189():105328. PubMed ID: 31958580
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net.
    Lei Y; Tian S; He X; Wang T; Wang B; Patel P; Jani AB; Mao H; Curran WJ; Liu T; Yang X
    Med Phys; 2019 Jul; 46(7):3194-3206. PubMed ID: 31074513
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An iterative multi-path fully convolutional neural network for automatic cardiac segmentation in cine MR images.
    Ma Z; Wu X; Wang X; Song Q; Yin Y; Cao K; Wang Y; Zhou J
    Med Phys; 2019 Dec; 46(12):5652-5665. PubMed ID: 31605627
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A novel convolutional neural network for kidney ultrasound images segmentation.
    Chen G; Yin J; Dai Y; Zhang J; Yin X; Cui L
    Comput Methods Programs Biomed; 2022 May; 218():106712. PubMed ID: 35248816
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Double-branched and area-constraint fully convolutional networks for automated serous retinal detachment segmentation in SD-OCT images.
    Gao K; Niu S; Ji Z; Wu M; Chen Q; Xu R; Yuan S; Fan W; Chen Y; Dong J
    Comput Methods Programs Biomed; 2019 Jul; 176():69-80. PubMed ID: 31200913
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 3D deeply supervised network for automated segmentation of volumetric medical images.
    Dou Q; Yu L; Chen H; Jin Y; Yang X; Qin J; Heng PA
    Med Image Anal; 2017 Oct; 41():40-54. PubMed ID: 28526212
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DENSE-INception U-net for medical image segmentation.
    Zhang Z; Wu C; Coleman S; Kerr D
    Comput Methods Programs Biomed; 2020 Aug; 192():105395. PubMed ID: 32163817
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A comparative study of pre-trained convolutional neural networks for semantic segmentation of breast tumors in ultrasound.
    Gómez-Flores W; Coelho de Albuquerque Pereira W
    Comput Biol Med; 2020 Nov; 126():104036. PubMed ID: 33059238
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Ultrasound image-based thyroid nodule automatic segmentation using convolutional neural networks.
    Ma J; Wu F; Jiang T; Zhao Q; Kong D
    Int J Comput Assist Radiol Surg; 2017 Nov; 12(11):1895-1910. PubMed ID: 28762196
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. 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]  

  • 19. Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks.
    Al-Masni MA; Al-Antari MA; Choi MT; Han SM; Kim TS
    Comput Methods Programs Biomed; 2018 Aug; 162():221-231. PubMed ID: 29903489
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 52.