BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

207 related articles for article (PubMed ID: 32746146)

  • 1. Zoom in Lesions for Better Diagnosis: Attention Guided Deformation Network for WCE Image Classification.
    Xing X; Yuan Y; Meng MQ
    IEEE Trans Med Imaging; 2020 Dec; 39(12):4047-4059. PubMed ID: 32746146
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Semi-supervised WCE image classification with adaptive aggregated attention.
    Guo X; Yuan Y
    Med Image Anal; 2020 Aug; 64():101733. PubMed ID: 32574987
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Application of Convolutional Neural Networks for Automated Ulcer Detection in Wireless Capsule Endoscopy Images.
    Alaskar H; Hussain A; Al-Aseem N; Liatsis P; Al-Jumeily D
    Sensors (Basel); 2019 Mar; 19(6):. PubMed ID: 30871162
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A deep convolutional neural network for bleeding detection in Wireless Capsule Endoscopy images.
    Xiao Jia ; Meng MQ
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():639-642. PubMed ID: 28268409
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep learning for registration of region of interest in consecutive wireless capsule endoscopy frames.
    Liao C; Wang C; Bai J; Lan L; Wu X
    Comput Methods Programs Biomed; 2021 Sep; 208():106189. PubMed ID: 34102560
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy.
    Vasilakakis MD; Iakovidis DK; Spyrou E; Koulaouzidis A
    Comput Math Methods Med; 2018; 2018():2026962. PubMed ID: 30250496
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Wireless capsule endoscopy multiclass classification using three-dimensional deep convolutional neural network model.
    Bordbar M; Helfroush MS; Danyali H; Ejtehadi F
    Biomed Eng Online; 2023 Dec; 22(1):124. PubMed ID: 38098015
    [TBL] [Abstract][Full Text] [Related]  

  • 9. RAt-CapsNet: A Deep Learning Network Utilizing Attention and Regional Information for Abnormality Detection in Wireless Capsule Endoscopy.
    Alam MJ; Rashid RB; Fattah SA; Saquib M
    IEEE J Transl Eng Health Med; 2022; 10():3300108. PubMed ID: 36032311
    [No Abstract]   [Full Text] [Related]  

  • 10. Hookworm Detection in Wireless Capsule Endoscopy Images With Deep Learning.
    He JY; Wu X; Jiang YG; Peng Q; Jain R
    IEEE Trans Image Process; 2018 May; 27(5):2379-2392. PubMed ID: 29470172
    [TBL] [Abstract][Full Text] [Related]  

  • 11. DSI-Net: Deep Synergistic Interaction Network for Joint Classification and Segmentation With Endoscope Images.
    Zhu M; Chen Z; Yuan Y
    IEEE Trans Med Imaging; 2021 Dec; 40(12):3315-3325. PubMed ID: 34033538
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A deep CNN model for anomaly detection and localization in wireless capsule endoscopy images.
    Jain S; Seal A; Ojha A; Yazidi A; Bures J; Tacheci I; Krejcar O
    Comput Biol Med; 2021 Oct; 137():104789. PubMed ID: 34455302
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multiple abnormality classification in wireless capsule endoscopy images based on EfficientNet using attention mechanism.
    Guo X; Zhang L; Hao Y; Zhang L; Liu Z; Liu J
    Rev Sci Instrum; 2021 Sep; 92(9):094102. PubMed ID: 34598534
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Colored Video Analysis in Wireless Capsule Endoscopy: A Survey of State-of-the-Art.
    Ashour AS; Dey N; Mohamed WS; Tromp JG; Sherratt RS; Shi F; Moraru L
    Curr Med Imaging; 2020; 16(9):1074-1084. PubMed ID: 32107996
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Bleeding detection in Wireless Capsule Endoscopy based on Probabilistic Neural Network.
    Pan G; Yan G; Qiu X; Cui J
    J Med Syst; 2011 Dec; 35(6):1477-84. PubMed ID: 20703770
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep learning for polyp recognition in wireless capsule endoscopy images.
    Yuan Y; Meng MQ
    Med Phys; 2017 Apr; 44(4):1379-1389. PubMed ID: 28160514
    [TBL] [Abstract][Full Text] [Related]  

  • 17. BP neural network classification for bleeding detection in wireless capsule endoscopy.
    Pan G; Yan G; Song X; Qiu X
    J Med Eng Technol; 2009; 33(7):575-81. PubMed ID: 19639509
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Low Complexity CNN Structure for Automatic Bleeding Zone Detection in Wireless Capsule Endoscopy Imaging.
    Hajabdollahi M; Esfandiarpoor R; Najarian K; Karimi N; Samavi S; Reza Soroushmehr SM
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():7227-7230. PubMed ID: 31947501
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Probability density function based modeling of spatial feature variation in capsule endoscopy data for automatic bleeding detection.
    Kundu AK; Fattah SA
    Comput Biol Med; 2019 Dec; 115():103478. PubMed ID: 31698239
    [TBL] [Abstract][Full Text] [Related]  

  • 20. High pooled performance of convolutional neural networks in computer-aided diagnosis of GI ulcers and/or hemorrhage on wireless capsule endoscopy images: a systematic review and meta-analysis.
    Mohan BP; Khan SR; Kassab LL; Ponnada S; Chandan S; Ali T; Dulai PS; Adler DG; Kochhar GS
    Gastrointest Endosc; 2021 Feb; 93(2):356-364.e4. PubMed ID: 32721487
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.