BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

134 related articles for article (PubMed ID: 35957432)

  • 1. Lightweight Compound Scaling Network for Nasopharyngeal Carcinoma Segmentation from MR Images.
    Liu Y; Han G; Liu X
    Sensors (Basel); 2022 Aug; 22(15):. PubMed ID: 35957432
    [TBL] [Abstract][Full Text] [Related]  

  • 2. WET-UNet: Wavelet integrated efficient transformer networks for nasopharyngeal carcinoma tumor segmentation.
    Zeng Y; Li J; Zhao Z; Liang W; Zeng P; Shen S; Zhang K; Shen C
    Sci Prog; 2024; 107(2):368504241232537. PubMed ID: 38567422
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Efficient fetal ultrasound image segmentation for automatic head circumference measurement using a lightweight deep convolutional neural network.
    Zeng W; Luo J; Cheng J; Lu Y
    Med Phys; 2022 Aug; 49(8):5081-5092. PubMed ID: 35536111
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Application of Artificial Intelligence in Radiotherapy of Nasopharyngeal Carcinoma with Magnetic Resonance Imaging.
    Zhao W; Zhang D; Mao X
    J Healthc Eng; 2022; 2022():4132989. PubMed ID: 35154619
    [TBL] [Abstract][Full Text] [Related]  

  • 5. CAFS: An Attention-Based Co-Segmentation Semi-Supervised Method for Nasopharyngeal Carcinoma Segmentation.
    Chen Y; Han G; Lin T; Liu X
    Sensors (Basel); 2022 Jul; 22(13):. PubMed ID: 35808548
    [TBL] [Abstract][Full Text] [Related]  

  • 6. TG-Net: Combining transformer and GAN for nasopharyngeal carcinoma tumor segmentation based on total-body uEXPLORER PET/CT scanner.
    Huang Z; Tang S; Chen Z; Wang G; Shen H; Zhou Y; Wang H; Fan W; Liang D; Hu Y; Hu Z
    Comput Biol Med; 2022 Sep; 148():105869. PubMed ID: 35905660
    [TBL] [Abstract][Full Text] [Related]  

  • 7. [Segmentation of organs at risk in nasopharyngeal cancer for radiotherapy using a self-adaptive Unet network].
    Yang X; Li X; Zhang X; Song F; Huang S; Xia Y
    Nan Fang Yi Ke Da Xue Xue Bao; 2020 Nov; 40(11):1579-1586. PubMed ID: 33243744
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies.
    Li C; Jing B; Ke L; Li B; Xia W; He C; Qian C; Zhao C; Mai H; Chen M; Cao K; Mo H; Guo L; Chen Q; Tang L; Qiu W; Yu Y; Liang H; Huang X; Liu G; Li W; Wang L; Sun R; Zou X; Guo S; Huang P; Luo D; Qiu F; Wu Y; Hua Y; Liu K; Lv S; Miao J; Xiang Y; Sun Y; Guo X; Lv X
    Cancer Commun (Lond); 2018 Sep; 38(1):59. PubMed ID: 30253801
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep learning-based accurate delineation of primary gross tumor volume of nasopharyngeal carcinoma on heterogeneous magnetic resonance imaging: A large-scale and multi-center study.
    Luo X; Liao W; He Y; Tang F; Wu M; Shen Y; Huang H; Song T; Li K; Zhang S; Zhang S; Wang G
    Radiother Oncol; 2023 Mar; 180():109480. PubMed ID: 36657723
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MFNet: Meta-learning based on frequency-space mix for MRI segmentation in nasopharyngeal carcinoma.
    Li Y; Chen Q; Li H; Wang S; Chen N; Han T; Wang K; Yu Q; Cao Z; Tang J
    J Cell Mol Med; 2024 May; 28(9):e18355. PubMed ID: 38685683
    [TBL] [Abstract][Full Text] [Related]  

  • 11. SeqSeg: A sequential method to achieve nasopharyngeal carcinoma segmentation free from background dominance.
    Tao G; Li H; Huang J; Han C; Chen J; Ruan G; Huang W; Hu Y; Dan T; Zhang B; He S; Liu L; Cai H
    Med Image Anal; 2022 May; 78():102381. PubMed ID: 35231849
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Continual improvement of nasopharyngeal carcinoma segmentation with less labeling effort.
    Men K; Chen X; Zhu J; Yang B; Zhang Y; Yi J; Jianrong Dai A
    Phys Med; 2020 Dec; 80():347-351. PubMed ID: 33271391
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep-learning-based detection and segmentation of organs at risk in nasopharyngeal carcinoma computed tomographic images for radiotherapy planning.
    Liang S; Tang F; Huang X; Yang K; Zhong T; Hu R; Liu S; Yuan X; Zhang Y
    Eur Radiol; 2019 Apr; 29(4):1961-1967. PubMed ID: 30302589
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic segmentation of organs-at-risks of nasopharynx cancer and lung cancer by cross-layer attention fusion network with TELD-Loss.
    Liu Z; Sun C; Wang H; Li Z; Gao Y; Lei W; Zhang S; Wang G; Zhang S
    Med Phys; 2021 Nov; 48(11):6987-7002. PubMed ID: 34608652
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A deep-learning method for generating synthetic kV-CT and improving tumor segmentation for helical tomotherapy of nasopharyngeal carcinoma.
    Chen X; Yang B; Li J; Zhu J; Ma X; Chen D; Hu Z; Men K; Dai J
    Phys Med Biol; 2021 Nov; 66(22):. PubMed ID: 34700300
    [No Abstract]   [Full Text] [Related]  

  • 16. Computer-aided diagnosis and regional segmentation of nasopharyngeal carcinoma based on multi-modality medical images.
    Qi Y; Li J; Chen H; Guo Y; Yin Y; Gong G; Wang L
    Int J Comput Assist Radiol Surg; 2021 Jun; 16(6):871-882. PubMed ID: 33782844
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Quantitative Comparisons of Deep-learning-based and Atlas-based Auto- segmentation of the Intermediate Risk Clinical Target Volume for Nasopharyngeal Carcinoma.
    He Y; Zhang S; Luo Y; Yu H; Fu Y; Wu Z; Jiang X; Li P
    Curr Med Imaging; 2022; 18(3):335-345. PubMed ID: 34455965
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Lightweight Network for Accurate Coronary Artery Segmentation Using X-Ray Angiograms.
    Tao X; Dang H; Zhou X; Xu X; Xiong D
    Front Public Health; 2022; 10():892418. PubMed ID: 35692314
    [TBL] [Abstract][Full Text] [Related]  

  • 19. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
    Zhu W; Huang Y; Zeng L; Chen X; Liu Y; Qian Z; Du N; Fan W; Xie X
    Med Phys; 2019 Feb; 46(2):576-589. PubMed ID: 30480818
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Medical lesion segmentation by combining multimodal images with modality weighted UNet.
    Zhu X; Wu Y; Hu H; Zhuang X; Yao J; Ou D; Li W; Song M; Feng N; Xu D
    Med Phys; 2022 Jun; 49(6):3692-3704. PubMed ID: 35312077
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.