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 *

171 related articles for article (PubMed ID: 33653266)

  • 1. InstantDL: an easy-to-use deep learning pipeline for image segmentation and classification.
    Waibel DJE; Shetab Boushehri S; Marr C
    BMC Bioinformatics; 2021 Mar; 22(1):103. PubMed ID: 33653266
    [TBL] [Abstract][Full Text] [Related]  

  • 2. MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning.
    Müller D; Kramer F
    BMC Med Imaging; 2021 Jan; 21(1):12. PubMed ID: 33461500
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
    Burton W; Myers C; Rullkoetter P
    Comput Methods Programs Biomed; 2020 Jun; 189():105328. PubMed ID: 31958580
    [TBL] [Abstract][Full Text] [Related]  

  • 4. CAST: A multi-scale convolutional neural network based automated hippocampal subfield segmentation toolbox.
    Yang Z; Zhuang X; Mishra V; Sreenivasan K; Cordes D
    Neuroimage; 2020 Sep; 218():116947. PubMed ID: 32474081
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improving segmentation and classification of renal tumors in small sample 3D CT images using transfer learning with convolutional neural networks.
    Zhu XL; Shen HB; Sun H; Duan LX; Xu YY
    Int J Comput Assist Radiol Surg; 2022 Jul; 17(7):1303-1311. PubMed ID: 35290645
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates.
    Gruber N; Galijasevic M; Regodic M; Grams AE; Siedentopf C; Steiger R; Hammerl M; Haltmeier M; Gizewski ER; Janjic T
    Artif Intell Med; 2022 Oct; 132():102384. PubMed ID: 36207089
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique.
    Verma PK; Kaur J
    J Imaging Inform Med; 2024 Aug; 37(4):1783-1799. PubMed ID: 38438695
    [TBL] [Abstract][Full Text] [Related]  

  • 8. UC-Hybrid: Uncertainty-based contrastive learning on hybrid network for medical image segmentation.
    Kim SH; Chung M
    Comput Methods Programs Biomed; 2024 Oct; 255():108367. PubMed ID: 39141962
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Deep Learning Pipeline for Nucleus Segmentation.
    Zaki G; Gudla PR; Lee K; Kim J; Ozbun L; Shachar S; Gadkari M; Sun J; Fraser IDC; Franco LM; Misteli T; Pegoraro G
    Cytometry A; 2020 Dec; 97(12):1248-1264. PubMed ID: 33141508
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain.
    Wang X; Zeng W; Yang X; Zhang Y; Fang C; Zeng S; Han Y; Fei P
    Elife; 2021 Jan; 10():. PubMed ID: 33459255
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.
    Liu F; Zhou Z; Jang H; Samsonov A; Zhao G; Kijowski R
    Magn Reson Med; 2018 Apr; 79(4):2379-2391. PubMed ID: 28733975
    [TBL] [Abstract][Full Text] [Related]  

  • 13. PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation.
    Wang G; Luo X; Gu R; Yang S; Qu Y; Zhai S; Zhao Q; Li K; Zhang S
    Comput Methods Programs Biomed; 2023 Apr; 231():107398. PubMed ID: 36773591
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Context aware deep learning for brain tumor segmentation, subtype classification, and survival prediction using radiology images.
    Pei L; Vidyaratne L; Rahman MM; Iftekharuddin KM
    Sci Rep; 2020 Nov; 10(1):19726. PubMed ID: 33184301
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Code-Free Machine Learning Solutions for Microscopy Image Processing: Deep Learning.
    Chechekhina E; Voloshin N; Kulebyakin K; Tyurin-Kuzmin P
    Tissue Eng Part A; 2024 Oct; 30(19-20):627-639. PubMed ID: 38556835
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.
    Roth HR; Lu L; Lay N; Harrison AP; Farag A; Sohn A; Summers RM
    Med Image Anal; 2018 Apr; 45():94-107. PubMed ID: 29427897
    [TBL] [Abstract][Full Text] [Related]  

  • 17. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation.
    Isensee F; Jaeger PF; Kohl SAA; Petersen J; Maier-Hein KH
    Nat Methods; 2021 Feb; 18(2):203-211. PubMed ID: 33288961
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images.
    Aatresh AA; Yatgiri RP; Chanchal AK; Kumar A; Ravi A; Das D; Bs R; Lal S; Kini J
    Comput Med Imaging Graph; 2021 Oct; 93():101975. PubMed ID: 34461375
    [TBL] [Abstract][Full Text] [Related]  

  • 20. SinGAN-Seg: Synthetic training data generation for medical image segmentation.
    Thambawita V; Salehi P; Sheshkal SA; Hicks SA; Hammer HL; Parasa S; Lange T; Halvorsen P; Riegler MA
    PLoS One; 2022; 17(5):e0267976. PubMed ID: 35500005
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.