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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1989 1
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1999 3
2000 1
2001 7
2002 5
2003 3
2004 3
2005 6
2006 4
2007 3
2008 11
2009 10
2010 7
2011 11
2012 12
2013 18
2014 28
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9,657 results

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Page 1
Symmetry-Aware Deep Learning for Cerebral Ventricle Segmentation With Intra-Ventricular Hemorrhage.
Hua Y, Yan Z, Kuang Z, Zhang H, Deng X, Yu L. Hua Y, et al. IEEE J Biomed Health Inform. 2022 Oct;26(10):5165-5176. doi: 10.1109/JBHI.2022.3190494. Epub 2022 Oct 4. IEEE J Biomed Health Inform. 2022. PMID: 35849684
Cerebral ventricles are one of the prominent structures in the brain, segmenting which can provide rich information for brain-related disease diagnosis. ...Moreover, we re-design an end-to-end version of symmetry-aware deep learning, making it m …
Cerebral ventricles are one of the prominent structures in the brain, segmenting which can provide rich information for bra …
Deep learning of early brain imaging to predict post-arrest electroencephalography.
Elmer J, Liu C, Pease M, Arefan D, Coppler PJ, Flickinger KL, Mettenburg JM, Baldwin ME, Barot N, Wu S. Elmer J, et al. Resuscitation. 2022 Mar;172:17-23. doi: 10.1016/j.resuscitation.2022.01.004. Epub 2022 Jan 15. Resuscitation. 2022. PMID: 35041875 Free PMC article.
Clinical ML models had moderate discrimination (test set AUCs 0.73-0.80). Image-based deep learning performed worse (test set AUCs 0.51-0.69), particularly discriminating benign from highly pathological findings. Adding image-based deep learn …
Clinical ML models had moderate discrimination (test set AUCs 0.73-0.80). Image-based deep learning performed worse (te …
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. Liu S, et al. Neuroimage. 2019 Sep;198:271-282. doi: 10.1016/j.neuroimage.2019.05.046. Epub 2019 May 20. Neuroimage. 2019. PMID: 31121296
The deep learning model was trained using 154 data sets, and the best models were selected using 25 validation data sets. ...This study demonstrates the potential of applying deep learning techniques to medical imaging for improving efficiency a …
The deep learning model was trained using 154 data sets, and the best models were selected using 25 validation data sets. ...T …
Deep Learning AI Applications in the Imaging of Glioma.
Zlochower A, Chow DS, Chang P, Khatri D, Boockvar JA, Filippi CG. Zlochower A, et al. Top Magn Reson Imaging. 2020 Apr;29(2):115-0. doi: 10.1097/RMR.0000000000000237. Top Magn Reson Imaging. 2020. PMID: 32271288 Review.
This manuscript will review emerging applications of artificial intelligence, specifically deep learning, and its application to glioblastoma multiforme (GBM), the most common primary malignant brain tumor. Current deep learning approaches, comm …
This manuscript will review emerging applications of artificial intelligence, specifically deep learning, and its application …
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. Xia P, et al. J Magn Reson Imaging. 2024 Sep;60(3):1165-1175. doi: 10.1002/jmri.29198. Epub 2023 Dec 27. J Magn Reson Imaging. 2024. PMID: 38149750
Specifically, quantitative susceptibility mapping (QSM) and deep learning were applied to detect CMBs in MRI. PURPOSE: To automatically detect CMB on QSM, we proposed a two-stage deep learning pipeline. ...Our results demonstrated the successful applic …
Specifically, quantitative susceptibility mapping (QSM) and deep learning were applied to detect CMBs in MRI. PURPOSE: To auto …
Deep learning-based correction for time truncation in cerebral computed tomography perfusion.
Ichikawa S, Ozaki M, Itadani H, Sugimori H, Kondo Y. Ichikawa S, et al. Radiol Phys Technol. 2024 Sep;17(3):666-678. doi: 10.1007/s12194-024-00818-6. Epub 2024 Jun 11. Radiol Phys Technol. 2024. PMID: 38861134
Cerebral computed tomography perfusion (CTP) imaging requires complete acquisition of contrast bolus inflow and washout in the brain parenchyma; however, time truncation undoubtedly occurs in clinical practice. ...We found that the image quality metric …
Cerebral computed tomography perfusion (CTP) imaging requires complete acquisition of contrast bolus inflow and washout in the …
Deep learning for cerebral angiography segmentation from non-contrast computed tomography.
Klimont M, Oronowicz-Jaśkowiak A, Flieger M, Rzeszutek J, Juszkat R, Jończyk-Potoczna K. Klimont M, et al. PLoS One. 2020 Jul 31;15(7):e0237092. doi: 10.1371/journal.pone.0237092. eCollection 2020. PLoS One. 2020. PMID: 32735633 Free PMC article.
There are known contraindications to administering iodinated contrast media, and in these cases, the patient has to undergo another examination to visualize cerebral arteries, such as magnetic resonance angiography. Deep learning for image segmentation …
There are known contraindications to administering iodinated contrast media, and in these cases, the patient has to undergo another examinat …
3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks.
Ren J, Wang X, Liu C, Sun H, Tong J, Lin M, Li J, Liang L, Yin F, Xie M, Liu Y. Ren J, et al. Sensors (Basel). 2023 Oct 9;23(19):8341. doi: 10.3390/s23198341. Sensors (Basel). 2023. PMID: 37837171 Free PMC article.
This study introduces a 3D AI algorithm, Brain Imaging Full Convolution Network (BIFCN), combining waveform modeling and deep learning for precise brain ultrasound reconstruction. ...The proposed 3D BIFCN algorithm provides a highly accurate and …
This study introduces a 3D AI algorithm, Brain Imaging Full Convolution Network (BIFCN), combining waveform modeling and de …
A Deep Learning-based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images.
Wang J, Gong R, Heidari S, Rogers M, Tani T, Abe H, Ichinohe N, Woodward A, Delmas PJ. Wang J, et al. Neuroinformatics. 2024 Oct;22(4):745-761. doi: 10.1007/s12021-024-09688-0. Epub 2024 Oct 17. Neuroinformatics. 2024. PMID: 39417954 Free PMC article.
Identifying these layers in neuroimaging data is important for understanding their global structure and to help understand the connectivity patterns of neurons in the brain. We studied Nissl-stained and myelin-stained slice images of the brain of the common m …
Identifying these layers in neuroimaging data is important for understanding their global structure and to help understand the connectivity …
Deep-fUS: A Deep Learning Platform for Functional Ultrasound Imaging of the Brain Using Sparse Data.
Di Ianni T, Airan RD. Di Ianni T, et al. IEEE Trans Med Imaging. 2022 Jul;41(7):1813-1825. doi: 10.1109/TMI.2022.3148728. Epub 2022 Jun 30. IEEE Trans Med Imaging. 2022. PMID: 35108201 Free PMC article.
Here we develop an image reconstruction method based on deep learning that significantly reduces the amount of data necessary while retaining imaging performance. ...We demonstrate that time series of power Doppler images can be reconstructed wi …
Here we develop an image reconstruction method based on deep learning that significantly reduces the amount of data nec …
9,657 results