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Journal Abstract Search

235 related items for PubMed ID: 31865021

  • 1. A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images.
    Xue Y, Farhat FG, Boukrina O, Barrett AM, Binder JR, Roshan UW, Graves WW.
    Neuroimage Clin; 2020; 25():102118. PubMed ID: 31865021
    [Abstract] [Full Text] [Related]

  • 2. [Fully Automatic Glioma Segmentation Algorithm of Magnetic Resonance Imaging Based on 3D-UNet With More Global Contextual Feature Extraction: An Improvement on Insufficient Extraction of Global Features].
    Tian H, Wang Y, Ji Y, Rahman MM.
    Sichuan Da Xue Xue Bao Yi Xue Ban; 2024 Mar 20; 55(2):447-454. PubMed ID: 38645864
    [Abstract] [Full Text] [Related]

  • 3. Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network.
    Tomita N, Jiang S, Maeder ME, Hassanpour S.
    Neuroimage Clin; 2020 Mar 20; 27():102276. PubMed ID: 32512401
    [Abstract] [Full Text] [Related]

  • 4. A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis.
    Salem M, Valverde S, Cabezas M, Pareto D, Oliver A, Salvi J, Rovira À, Lladó X.
    Neuroimage Clin; 2020 Mar 20; 25():102149. PubMed ID: 31918065
    [Abstract] [Full Text] [Related]

  • 5. Are multi-contrast magnetic resonance images necessary for segmenting multiple sclerosis brains? A large cohort study based on deep learning.
    Narayana PA, Coronado I, Sujit SJ, Sun X, Wolinsky JS, Gabr RE.
    Magn Reson Imaging; 2020 Jan 20; 65():8-14. PubMed ID: 31670238
    [Abstract] [Full Text] [Related]

  • 6. An appraisal of the performance of AI tools for chronic stroke lesion segmentation.
    Ahmed R, Al Shehhi A, Hassan B, Werghi N, Seghier ML.
    Comput Biol Med; 2023 Sep 20; 164():107302. PubMed ID: 37572443
    [Abstract] [Full Text] [Related]

  • 7. Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.
    Valverde S, Cabezas M, Roura E, González-Villà S, Pareto D, Vilanova JC, Ramió-Torrentà L, Rovira À, Oliver A, Lladó X.
    Neuroimage; 2017 Jul 15; 155():159-168. PubMed ID: 28435096
    [Abstract] [Full Text] [Related]

  • 8. Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss.
    Xu Y, Klyuzhin I, Harsini S, Ortiz A, Zhang S, Bénard F, Dodhia R, Uribe CF, Rahmim A, Lavista Ferres J.
    Comput Biol Med; 2023 May 15; 158():106882. PubMed ID: 37037147
    [Abstract] [Full Text] [Related]

  • 9. D-UNet: A Dimension-Fusion U Shape Network for Chronic Stroke Lesion Segmentation.
    Zhou Y, Huang W, Dong P, Xia Y, Wang S.
    IEEE/ACM Trans Comput Biol Bioinform; 2021 May 15; 18(3):940-950. PubMed ID: 31502985
    [Abstract] [Full Text] [Related]

  • 10. Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.
    Lavdas I, Glocker B, Kamnitsas K, Rueckert D, Mair H, Sandhu A, Taylor SA, Aboagye EO, Rockall AG.
    Med Phys; 2017 Oct 15; 44(10):5210-5220. PubMed ID: 28756622
    [Abstract] [Full Text] [Related]

  • 11. Identification and Diagnosis of Cerebral Stroke through Deep Convolutional Neural Network-Based Multimodal MRI Images.
    Pan Y, Zhang H, Yang J, Guo J, Yang Z, Wang J, Song G.
    Contrast Media Mol Imaging; 2021 Oct 15; 2021():7598613. PubMed ID: 34381322
    [Abstract] [Full Text] [Related]

  • 12. CNN-Res: deep learning framework for segmentation of acute ischemic stroke lesions on multimodal MRI images.
    Gheibi Y, Shirini K, Razavi SN, Farhoudi M, Samad-Soltani T.
    BMC Med Inform Decis Mak; 2023 Sep 26; 23(1):192. PubMed ID: 37752508
    [Abstract] [Full Text] [Related]

  • 13. Automated multimodal segmentation of acute ischemic stroke lesions on clinical MR images.
    Moon HS, Heffron L, Mahzarnia A, Obeng-Gyasi B, Holbrook M, Badea CT, Feng W, Badea A.
    Magn Reson Imaging; 2022 Oct 26; 92():45-57. PubMed ID: 35688400
    [Abstract] [Full Text] [Related]

  • 14. Accurate and robust segmentation of neuroanatomy in T1-weighted MRI by combining spatial priors with deep convolutional neural networks.
    Novosad P, Fonov V, Collins DL, Alzheimer's Disease Neuroimaging Initiative†.
    Hum Brain Mapp; 2020 Feb 01; 41(2):309-327. PubMed ID: 31633863
    [Abstract] [Full Text] [Related]

  • 15. Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.
    Kleesiek J, Urban G, Hubert A, Schwarz D, Maier-Hein K, Bendszus M, Biller A.
    Neuroimage; 2016 Apr 01; 129():460-469. PubMed ID: 26808333
    [Abstract] [Full Text] [Related]

  • 16. 3D hemisphere-based convolutional neural network for whole-brain MRI segmentation.
    Yee E, Ma D, Popuri K, Chen S, Lee H, Chow V, Ma C, Wang L, Beg MF, Alzheimer’s Disease Neuroimaging Initiative, Australian Imaging Biomarkers and Lifestyle flagship study of ageing.
    Comput Med Imaging Graph; 2022 Jan 01; 95():102000. PubMed ID: 34839147
    [Abstract] [Full Text] [Related]

  • 17. Splenomegaly Segmentation on Multi-Modal MRI Using Deep Convolutional Networks.
    Huo Y, Xu Z, Bao S, Bermudez C, Moon H, Parvathaneni P, Moyo TK, Savona MR, Assad A, Abramson RG, Landman BA.
    IEEE Trans Med Imaging; 2019 May 01; 38(5):1185-1196. PubMed ID: 30442602
    [Abstract] [Full Text] [Related]

  • 18. Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans.
    Griffis JC, Allendorfer JB, Szaflarski JP.
    J Neurosci Methods; 2016 Jan 15; 257():97-108. PubMed ID: 26432931
    [Abstract] [Full Text] [Related]

  • 19. PSACNN: Pulse sequence adaptive fast whole brain segmentation.
    Jog A, Hoopes A, Greve DN, Van Leemput K, Fischl B.
    Neuroimage; 2019 Oct 01; 199():553-569. PubMed ID: 31129303
    [Abstract] [Full Text] [Related]

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