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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

477 related articles for article (PubMed ID: 35717560)

  • 81. Two-stage lung nodule detection framework using enhanced UNet and convolutional LSTM networks in CT images.
    Akila Agnes S; Anitha J; Arun Solomon A
    Comput Biol Med; 2022 Oct; 149():106059. PubMed ID: 36087510
    [TBL] [Abstract][Full Text] [Related]  

  • 82. Better performance of deep learning pulmonary nodule detection using chest radiography with pixel level labels in reference to computed tomography: data quality matters.
    Kim JY; Ryu WS; Kim D; Kim EY
    Sci Rep; 2024 Jul; 14(1):15967. PubMed ID: 38987309
    [TBL] [Abstract][Full Text] [Related]  

  • 83. [Automatic segmentation of head and neck organs at risk based on three-dimensional U-NET deep convolutional neural network].
    Dai X; Wang X; Du L; Ma N; Xu S; Cai B; Wang S; Wang Z; Qu B
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2020 Feb; 37(1):136-141. PubMed ID: 32096387
    [TBL] [Abstract][Full Text] [Related]  

  • 84. A cascaded dual-pathway residual network for lung nodule segmentation in CT images.
    Liu H; Cao H; Song E; Ma G; Xu X; Jin R; Jin Y; Hung CC
    Phys Med; 2019 Jul; 63():112-121. PubMed ID: 31221402
    [TBL] [Abstract][Full Text] [Related]  

  • 85. Knee menisci segmentation and relaxometry of 3D ultrashort echo time cones MR imaging using attention U-Net with transfer learning.
    Byra M; Wu M; Zhang X; Jang H; Ma YJ; Chang EY; Shah S; Du J
    Magn Reson Med; 2020 Mar; 83(3):1109-1122. PubMed ID: 31535731
    [TBL] [Abstract][Full Text] [Related]  

  • 86. Automatic segmentation of lung tumors on CT images based on a 2D & 3D hybrid convolutional neural network.
    Gan W; Wang H; Gu H; Duan Y; Shao Y; Chen H; Feng A; Huang Y; Fu X; Ying Y; Quan H; Xu Z
    Br J Radiol; 2021 Oct; 94(1126):20210038. PubMed ID: 34347535
    [TBL] [Abstract][Full Text] [Related]  

  • 87. Lung-PNet: An Automated Deep Learning Model for the Diagnosis of Invasive Adenocarcinoma in Pure Ground-Glass Nodules on Chest CT.
    Qi K; Wang K; Wang X; Zhang YD; Lin G; Zhang X; Liu H; Huang W; Wu J; Zhao K; Liu J; Li J; Zhang X
    AJR Am J Roentgenol; 2024 Jan; 222(1):e2329674. PubMed ID: 37493322
    [No Abstract]   [Full Text] [Related]  

  • 88. Pulmonary nodule segmentation with CT sample synthesis using adversarial networks.
    Qin Y; Zheng H; Huang X; Yang J; Zhu YM
    Med Phys; 2019 Mar; 46(3):1218-1229. PubMed ID: 30575046
    [TBL] [Abstract][Full Text] [Related]  

  • 89. Lung nodule detection in chest X-rays using synthetic ground-truth data comparing CNN-based diagnosis to human performance.
    Schultheiss M; Schmette P; Bodden J; Aichele J; Müller-Leisse C; Gassert FG; Gassert FT; Gawlitza JF; Hofmann FC; Sasse D; von Schacky CE; Ziegelmayer S; De Marco F; Renger B; Makowski MR; Pfeiffer F; Pfeiffer D
    Sci Rep; 2021 Aug; 11(1):15857. PubMed ID: 34349135
    [TBL] [Abstract][Full Text] [Related]  

  • 90. An adaptive morphology based segmentation technique for lung nodule detection in thoracic CT image.
    Halder A; Chatterjee S; Dey D; Kole S; Munshi S
    Comput Methods Programs Biomed; 2020 Dec; 197():105720. PubMed ID: 32877818
    [TBL] [Abstract][Full Text] [Related]  

  • 91. Development and clinical application of deep learning model for lung nodules screening on CT images.
    Cui S; Ming S; Lin Y; Chen F; Shen Q; Li H; Chen G; Gong X; Wang H
    Sci Rep; 2020 Aug; 10(1):13657. PubMed ID: 32788705
    [TBL] [Abstract][Full Text] [Related]  

  • 92. Accurate object localization facilitates automatic esophagus segmentation in deep learning.
    Li Z; Gan G; Guo J; Zhan W; Chen L
    Radiat Oncol; 2024 May; 19(1):55. PubMed ID: 38735947
    [TBL] [Abstract][Full Text] [Related]  

  • 93. Lung Segmentation on HRCT and Volumetric CT for Diffuse Interstitial Lung Disease Using Deep Convolutional Neural Networks.
    Park B; Park H; Lee SM; Seo JB; Kim N
    J Digit Imaging; 2019 Dec; 32(6):1019-1026. PubMed ID: 31396776
    [TBL] [Abstract][Full Text] [Related]  

  • 94. Curv-Net: Curvilinear structure segmentation network based on selective kernel and multi-Bi-ConvLSTM.
    He Y; Sun H; Yi Y; Chen W; Kong J; Zheng C
    Med Phys; 2022 May; 49(5):3144-3158. PubMed ID: 35172016
    [TBL] [Abstract][Full Text] [Related]  

  • 95. Automated Lung Nodule Detection and Classification Using Deep Learning Combined with Multiple Strategies.
    Nasrullah N; Sang J; Alam MS; Mateen M; Cai B; Hu H
    Sensors (Basel); 2019 Aug; 19(17):. PubMed ID: 31466261
    [TBL] [Abstract][Full Text] [Related]  

  • 96. Development and Validation of a Modified Three-Dimensional U-Net Deep-Learning Model for Automated Detection of Lung Nodules on Chest CT Images From the Lung Image Database Consortium and Japanese Datasets.
    Suzuki K; Otsuka Y; Nomura Y; Kumamaru KK; Kuwatsuru R; Aoki S
    Acad Radiol; 2022 Feb; 29 Suppl 2():S11-S17. PubMed ID: 32839096
    [TBL] [Abstract][Full Text] [Related]  

  • 97. Deep convolutional neural network for segmentation of thoracic organs-at-risk using cropped 3D images.
    Feng X; Qing K; Tustison NJ; Meyer CH; Chen Q
    Med Phys; 2019 May; 46(5):2169-2180. PubMed ID: 30830685
    [TBL] [Abstract][Full Text] [Related]  

  • 98. Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.
    Jiang J; Hu YC; Tyagi N; Zhang P; Rimner A; Deasy JO; Veeraraghavan H
    Med Phys; 2019 Oct; 46(10):4392-4404. PubMed ID: 31274206
    [TBL] [Abstract][Full Text] [Related]  

  • 99. Automated Lung Segmentation on Chest Computed Tomography Images with Extensive Lung Parenchymal Abnormalities Using a Deep Neural Network.
    Yoo SJ; Yoon SH; Lee JH; Kim KH; Choi HI; Park SJ; Goo JM
    Korean J Radiol; 2021 Mar; 22(3):476-488. PubMed ID: 33169549
    [TBL] [Abstract][Full Text] [Related]  

  • 100. A comparison between deep learning convolutional neural networks and radiologists in the differentiation of benign and malignant thyroid nodules on CT images.
    Zhao HB; Liu C; Ye J; Chang LF; Xu Q; Shi BW; Liu LL; Yin YL; Shi BB
    Endokrynol Pol; 2021; 72(3):217-225. PubMed ID: 33619712
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 24.