BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

563 related articles for article (PubMed ID: 27847543)

  • 1. Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification.
    Ribeiro E; Uhl A; Wimmer G; Häfner M
    Comput Math Methods Med; 2016; 2016():6584725. PubMed ID: 27847543
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
    Tajbakhsh N; Shin JY; Gurudu SR; Hurst RT; Kendall CB; Gotway MB; Jianming Liang
    IEEE Trans Med Imaging; 2016 May; 35(5):1299-1312. PubMed ID: 26978662
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Directional wavelet based features for colonic polyp classification.
    Wimmer G; Tamaki T; Tischendorf JJ; Häfner M; Yoshida S; Tanaka S; Uhl A
    Med Image Anal; 2016 Jul; 31():16-36. PubMed ID: 26948110
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.
    Urban G; Tripathi P; Alkayali T; Mittal M; Jalali F; Karnes W; Baldi P
    Gastroenterology; 2018 Oct; 155(4):1069-1078.e8. PubMed ID: 29928897
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.
    Komeda Y; Handa H; Watanabe T; Nomura T; Kitahashi M; Sakurai T; Okamoto A; Minami T; Kono M; Arizumi T; Takenaka M; Hagiwara S; Matsui S; Nishida N; Kashida H; Kudo M
    Oncology; 2017; 93 Suppl 1():30-34. PubMed ID: 29258081
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Quest for the best endoscopic imaging modality for computer-assisted colonic polyp staging.
    Wimmer G; Gadermayr M; Wolkersdörfer G; Kwitt R; Tamaki T; Tischendorf J; Häfner M; Yoshida S; Tanaka S; Merhof D; Uhl A
    World J Gastroenterol; 2019 Mar; 25(10):1197-1209. PubMed ID: 30886503
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automatic Detection and Classification of Colorectal Polyps by Transferring Low-Level CNN Features From Nonmedical Domain.
    Zhang R; Zheng Y; Mak TW; Yu R; Wong SH; Lau JY; Poon CC
    IEEE J Biomed Health Inform; 2017 Jan; 21(1):41-47. PubMed ID: 28114040
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.
    Shin HC; Roth HR; Gao M; Lu L; Xu Z; Nogues I; Yao J; Mollura D; Summers RM
    IEEE Trans Med Imaging; 2016 May; 35(5):1285-98. PubMed ID: 26886976
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep Convolutional Neural Network for Ulcer Recognition in Wireless Capsule Endoscopy: Experimental Feasibility and Optimization.
    Wang S; Xing Y; Zhang L; Gao H; Zhang H
    Comput Math Methods Med; 2019; 2019():7546215. PubMed ID: 31641370
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Integrating Online and Offline Three-Dimensional Deep Learning for Automated Polyp Detection in Colonoscopy Videos.
    Lequan Yu ; Hao Chen ; Qi Dou ; Jing Qin ; Pheng Ann Heng
    IEEE J Biomed Health Inform; 2017 Jan; 21(1):65-75. PubMed ID: 28114049
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep learning with convolutional neural network in radiology.
    Yasaka K; Akai H; Kunimatsu A; Kiryu S; Abe O
    Jpn J Radiol; 2018 Apr; 36(4):257-272. PubMed ID: 29498017
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Local fractal dimension based approaches for colonic polyp classification.
    Häfner M; Tamaki T; Tanaka S; Uhl A; Wimmer G; Yoshida S
    Med Image Anal; 2015 Dec; 26(1):92-107. PubMed ID: 26385078
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Skin lesion classification with ensembles of deep convolutional neural networks.
    Harangi B
    J Biomed Inform; 2018 Oct; 86():25-32. PubMed ID: 30103029
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automated Polyp Detection in Colonoscopy Videos Using Shape and Context Information.
    Tajbakhsh N; Gurudu SR; Liang J
    IEEE Trans Med Imaging; 2016 Feb; 35(2):630-44. PubMed ID: 26462083
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Combining deep residual neural network features with supervised machine learning algorithms to classify diverse food image datasets.
    McAllister P; Zheng H; Bond R; Moorhead A
    Comput Biol Med; 2018 Apr; 95():217-233. PubMed ID: 29549733
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification.
    Kumar A; Kim J; Lyndon D; Fulham M; Feng D
    IEEE J Biomed Health Inform; 2017 Jan; 21(1):31-40. PubMed ID: 28114041
    [TBL] [Abstract][Full Text] [Related]  

  • 17. White blood cells detection and classification based on regional convolutional neural networks.
    Kutlu H; Avci E; Özyurt F
    Med Hypotheses; 2020 Feb; 135():109472. PubMed ID: 31760248
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Review of computational methods for the detection and classification of polyps in colonoscopy imaging.
    Sánchez-Montes C; Bernal J; García-Rodríguez A; Córdova H; Fernández-Esparrach G
    Gastroenterol Hepatol; 2020 Apr; 43(4):222-232. PubMed ID: 32143918
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An improved deep learning approach and its applications on colonic polyp images detection.
    Wang W; Tian J; Zhang C; Luo Y; Wang X; Li J
    BMC Med Imaging; 2020 Jul; 20(1):83. PubMed ID: 32698839
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Transfer learning for classification of cardiovascular tissues in histological images.
    Mazo C; Bernal J; Trujillo M; Alegre E
    Comput Methods Programs Biomed; 2018 Oct; 165():69-76. PubMed ID: 30337082
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 29.