119 related articles for article (PubMed ID: 38494702)
1. 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]
2. 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]
3. Automated detection of cerebral microbleeds on MR images using knowledge distillation framework.
Sundaresan V; Arthofer C; Zamboni G; Murchison AG; Dineen RA; Rothwell PM; Auer DP; Wang C; Miller KL; Tendler BC; Alfaro-Almagro F; Sotiropoulos SN; Sprigg N; Griffanti L; Jenkinson M
Front Neuroinform; 2023; 17():1204186. PubMed ID: 37492242
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. 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]
7. 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]
8. Automatic detection of cerebral microbleeds using susceptibility weighted imaging and artificial intelligence.
Luo Y; Gao K; Fawaz M; Wu B; Zhong Y; Zhou Y; Haacke EM; Dai Y; Liu S
Quant Imaging Med Surg; 2024 Mar; 14(3):2640-2654. PubMed ID: 38545040
[TBL] [Abstract][Full Text] [Related]
9. Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks.
Qi Dou ; Hao Chen ; Lequan Yu ; Lei Zhao ; Jing Qin ; Defeng Wang ; Mok VC; Lin Shi ; Pheng-Ann Heng
IEEE Trans Med Imaging; 2016 May; 35(5):1182-1195. PubMed ID: 26886975
[TBL] [Abstract][Full Text] [Related]
10. Automated Detection of Candidate Subjects With Cerebral Microbleeds Using Machine Learning.
Sundaresan V; Arthofer C; Zamboni G; Dineen RA; Rothwell PM; Sotiropoulos SN; Auer DP; Tozer DJ; Markus HS; Miller KL; Dragonu I; Sprigg N; Alfaro-Almagro F; Jenkinson M; Griffanti L
Front Neuroinform; 2021; 15():777828. PubMed ID: 35126079
[TBL] [Abstract][Full Text] [Related]
11. 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; 2023 Dec; ():. PubMed ID: 38149750
[TBL] [Abstract][Full Text] [Related]
12. Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique.
Teramoto A; Fujita H; Yamamuro O; Tamaki T
Med Phys; 2016 Jun; 43(6):2821-2827. PubMed ID: 27277030
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. 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]
16. Quantitative assessment and correlation analysis of cerebral microbleed distribution and leukoaraiosis in stroke outpatients.
Yang Q; Yang Y; Li C; Li J; Liu X; Wang A; Zhao J; Wang M; Zeng X; Fan D
Neurol Res; 2015 May; 37(5):403-9. PubMed ID: 25875577
[TBL] [Abstract][Full Text] [Related]
17. A Two Cascaded Network Integrating Regional-based YOLO and 3D-CNN for Cerebral Microbleeds Detection.
Al-Masni MA; Kim WR; Kim EY; Noh Y; Kim DH
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1055-1058. PubMed ID: 33018167
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. Comparison of ESWAN, SWI-SPGR, and 2D T2*-weighted GRE sequence for depicting cerebral microbleeds.
Guo LF; Wang G; Zhu XY; Liu C; Cui L
Clin Neuroradiol; 2013 Jun; 23(2):121-7. PubMed ID: 23212660
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
