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 *

295 related articles for article (PubMed ID: 30140608)

  • 1. A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning.
    Morrison MA; Payabvash S; Chen Y; Avadiappan S; Shah M; Zou X; Hess CP; Lupo JM
    Neuroimage Clin; 2018; 20():498-505. PubMed ID: 30140608
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping.
    Xia P; Hui ES; Chua BJ; Huang F; Wang Z; Zhang H; Yu H; Lau KK; Mak HKF; Cao P
    J Magn Reson Imaging; 2024 Sep; 60(3):1165-1175. PubMed ID: 38149750
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automated detection of cerebral microbleeds in patients with Traumatic Brain Injury.
    van den Heuvel TL; van der Eerden AW; Manniesing R; Ghafoorian M; Tan T; Andriessen TM; Vande Vyvere T; van den Hauwe L; Ter Haar Romeny BM; Goraj BM; Platel B
    Neuroimage Clin; 2016; 12():241-51. PubMed ID: 27489772
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Computer-aided detection of cerebral microbleeds in susceptibility-weighted imaging.
    Fazlollahi A; Meriaudeau F; Giancardo L; Villemagne VL; Rowe CC; Yates P; Salvado O; Bourgeat P;
    Comput Med Imaging Graph; 2015 Dec; 46 Pt 3():269-76. PubMed ID: 26560677
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Cerebral microbleed detection using Susceptibility Weighted Imaging and deep learning.
    Liu S; Utriainen D; Chai C; Chen Y; Wang L; Sethi SK; Xia S; Haacke EM
    Neuroimage; 2019 Sep; 198():271-282. PubMed ID: 31121296
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automated detection of cerebral microbleeds in MR images: A two-stage deep learning approach.
    Al-Masni MA; Kim WR; Kim EY; Noh Y; Kim DH
    Neuroimage Clin; 2020; 28():102464. PubMed ID: 33395960
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Synthetic microbleeds generation for classifier training without ground truth.
    Momeni S; Fazlollahi A; Yates P; Rowe C; Gao Y; Liew AW; Salvado O
    Comput Methods Programs Biomed; 2021 Aug; 207():106127. PubMed ID: 34051412
    [TBL] [Abstract][Full Text] [Related]  

  • 8. CMB-HUNT: Automatic detection of cerebral microbleeds using a deep neural network.
    Suwalska A; Wang Y; Yuan Z; Jiang Y; Zhu D; Chen J; Cui M; Chen X; Suo C; Polanska J
    Comput Biol Med; 2022 Dec; 151(Pt A):106233. PubMed ID: 36370581
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improved cerebral microbleeds detection using their magnetic signature on T2*-phase-contrast: A comparison study in a clinical setting.
    Kaaouana T; Bertrand A; Ouamer F; Law-Ye B; Pyatigorskaya N; Bouyahia A; Thiery N; Dufouil C; Delmaire C; Dormont D; de Rochefort L; Chupin M
    Neuroimage Clin; 2017; 15():274-283. PubMed ID: 28560152
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Novel Approaches to Detection of Cerebral Microbleeds: Single Deep Learning Model to Achieve a Balanced Performance.
    Myung MJ; Lee KM; Kim HG; Oh J; Lee JY; Shin I; Kim EJ; Lee JS
    J Stroke Cerebrovasc Dis; 2021 Sep; 30(9):105886. PubMed ID: 34175642
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computer-aided detection of radiation-induced cerebral microbleeds on susceptibility-weighted MR images.
    Bian W; Hess CP; Chang SM; Nelson SJ; Lupo JM
    Neuroimage Clin; 2013; 2():282-90. PubMed ID: 24179783
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Naïve Bayes classifier assisted automated detection of cerebral microbleeds in susceptibility-weighted imaging brain images.
    Ateeq T; Faheem ZB; Ghoneimy M; Ali J; Li Y; Baz A
    Biochem Cell Biol; 2023 Dec; 101(6):562-573. PubMed ID: 37639730
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Susceptibility-weighted imaging is more reliable than T2*-weighted gradient-recalled echo MRI for detecting microbleeds.
    Cheng AL; Batool S; McCreary CR; Lauzon ML; Frayne R; Goyal M; Smith EE
    Stroke; 2013 Oct; 44(10):2782-6. PubMed ID: 23920014
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automated Detection of Cerebral Microbleeds on Two-dimensional Gradient-recalled Echo T2* Weighted Images Using a Morphology Filter Bank and Convolutional Neural Network.
    Nishioka N; Shimizu Y; Shirai T; Ochi H; Bito Y; Watanabe K; Kameda H; Harada T; Kudo K
    Magn Reson Med Sci; 2024 Mar; ():. PubMed ID: 38494702
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Efficient detection of cerebral microbleeds on 7.0 T MR images using the radial symmetry transform.
    Kuijf HJ; de Bresser J; Geerlings MI; Conijn MM; Viergever MA; Biessels GJ; Vincken KL
    Neuroimage; 2012 Feb; 59(3):2266-73. PubMed ID: 21985903
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep learning-assisted IoMT framework for cerebral microbleed detection.
    Ali Z; Naz S; Yasmin S; Bukhari M; Kim M
    Heliyon; 2023 Dec; 9(12):e22879. PubMed ID: 38125517
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Risk of Symptomatic Intracerebral Hemorrhage After Intravenous Thrombolysis in Patients With Acute Ischemic Stroke and High Cerebral Microbleed Burden: A Meta-analysis.
    Tsivgoulis G; Zand R; Katsanos AH; Turc G; Nolte CH; Jung S; Cordonnier C; Fiebach JB; Scheitz JF; Klinger-Gratz PP; Oppenheim C; Goyal N; Safouris A; Mattle HP; Alexandrov AW; Schellinger PD; Alexandrov AV
    JAMA Neurol; 2016 Jun; 73(6):675-83. PubMed ID: 27088650
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated detection of cerebral microbleeds via segmentation in susceptibility-weighted images of patients with traumatic brain injury.
    Koschmieder K; Paul MM; van den Heuvel TLA; van der Eerden AW; van Ginneken B; Manniesing R
    Neuroimage Clin; 2022; 35():103027. PubMed ID: 35597029
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Semi-Automated Detection of Cerebral Microbleeds on 3.0 T MR Images.
    Kuijf HJ; Brundel M; de Bresser J; van Veluw SJ; Heringa SM; Viergever MA; Biessels GJ; Vincken KL
    PLoS One; 2013; 8(6):e66610. PubMed ID: 23805246
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automatic cerebral microbleeds detection from MR images via Independent Subspace Analysis based hierarchical features.
    Qi Dou ; Hao Chen ; Lequan Yu ; Lin Shi ; Defeng Wang ; Mok VC; Pheng Ann Heng
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():7933-6. PubMed ID: 26738132
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.