BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

947 related articles for article (PubMed ID: 32818626)

  • 1. Deep computational pathology in breast cancer.
    Duggento A; Conti A; Mauriello A; Guerrisi M; Toschi N
    Semin Cancer Biol; 2021 Jul; 72():226-237. PubMed ID: 32818626
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Pathology Image Analysis Using Segmentation Deep Learning Algorithms.
    Wang S; Yang DM; Rong R; Zhan X; Xiao G
    Am J Pathol; 2019 Sep; 189(9):1686-1698. PubMed ID: 31199919
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep learning approaches for breast cancer detection in histopathology images: A review.
    Priya C V L; V G B; B R V; Ramachandran S
    Cancer Biomark; 2024; 40(1):1-25. PubMed ID: 38517775
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep learning for colon cancer histopathological images analysis.
    Ben Hamida A; Devanne M; Weber J; Truntzer C; Derangère V; Ghiringhelli F; Forestier G; Wemmert C
    Comput Biol Med; 2021 Sep; 136():104730. PubMed ID: 34375901
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Semantic Integrative Digital Pathology: Insights into Microsemiological Semantics and Image Analysis Scalability.
    Racoceanu D; Capron F
    Pathobiology; 2016; 83(2-3):148-55. PubMed ID: 27100713
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Recent advances and clinical applications of deep learning in medical image analysis.
    Chen X; Wang X; Zhang K; Fung KM; Thai TC; Moore K; Mannel RS; Liu H; Zheng B; Qiu Y
    Med Image Anal; 2022 Jul; 79():102444. PubMed ID: 35472844
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis.
    Kosaraju SC; Hao J; Koh HM; Kang M
    Methods; 2020 Jul; 179():3-13. PubMed ID: 32442672
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Operational greenhouse-gas emissions of deep learning in digital pathology: a modelling study.
    Vafaei Sadr A; Bülow R; von Stillfried S; Schmitz NEJ; Pilva P; Hölscher DL; Ha PP; Schweiker M; Boor P
    Lancet Digit Health; 2024 Jan; 6(1):e58-e69. PubMed ID: 37996339
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases.
    Janowczyk A; Madabhushi A
    J Pathol Inform; 2016; 7():29. PubMed ID: 27563488
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automated curation of large-scale cancer histopathology image datasets using deep learning.
    Hilgers L; Ghaffari Laleh N; West NP; Westwood A; Hewitt KJ; Quirke P; Grabsch HI; Carrero ZI; Matthaei E; Loeffler CML; Brinker TJ; Yuan T; Brenner H; Brobeil A; Hoffmeister M; Kather JN
    Histopathology; 2024 Jun; 84(7):1139-1153. PubMed ID: 38409878
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Recent developments in cervical cancer diagnosis using deep learning on whole slide images: An Overview of models, techniques, challenges and future directions.
    Sambyal D; Sarwar A
    Micron; 2023 Oct; 173():103520. PubMed ID: 37556898
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis.
    Wang X; Chen H; Gan C; Lin H; Dou Q; Tsougenis E; Huang Q; Cai M; Heng PA
    IEEE Trans Cybern; 2020 Sep; 50(9):3950-3962. PubMed ID: 31484154
    [TBL] [Abstract][Full Text] [Related]  

  • 13. RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge.
    Wodzinski M; Marini N; Atzori M; Müller H
    Comput Methods Programs Biomed; 2024 Jun; 250():108187. PubMed ID: 38657383
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep Learning in Microscopy Image Analysis: A Survey.
    Fuyong Xing ; Yuanpu Xie ; Hai Su ; Fujun Liu ; Lin Yang
    IEEE Trans Neural Netw Learn Syst; 2018 Oct; 29(10):4550-4568. PubMed ID: 29989994
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Image analysis and machine learning in digital pathology: Challenges and opportunities.
    Madabhushi A; Lee G
    Med Image Anal; 2016 Oct; 33():170-175. PubMed ID: 27423409
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification.
    Marini N; Otálora S; Müller H; Atzori M
    Med Image Anal; 2021 Oct; 73():102165. PubMed ID: 34303169
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis.
    Salvi M; Acharya UR; Molinari F; Meiburger KM
    Comput Biol Med; 2021 Jan; 128():104129. PubMed ID: 33254082
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.
    Rong R; Sheng H; Jin KW; Wu F; Luo D; Wen Z; Tang C; Yang DM; Jia L; Amgad M; Cooper LAD; Xie Y; Zhan X; Wang S; Xiao G
    Mod Pathol; 2023 Aug; 36(8):100196. PubMed ID: 37100227
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A survey on deep learning in medical image analysis.
    Litjens G; Kooi T; Bejnordi BE; Setio AAA; Ciompi F; Ghafoorian M; van der Laak JAWM; van Ginneken B; Sánchez CI
    Med Image Anal; 2017 Dec; 42():60-88. PubMed ID: 28778026
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.
    Baig R; Bibi M; Hamid A; Kausar S; Khalid S
    Curr Med Imaging; 2020; 16(5):513-533. PubMed ID: 32484086
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 48.