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Journal Abstract Search

442 related items for PubMed ID: 36107021

  • 1. Super-resolution of brain tumor MRI images based on deep learning.
    Zhou Z, Ma A, Feng Q, Wang R, Cheng L, Chen X, Yang X, Liao K, Miao Y, Qiu Y.
    J Appl Clin Med Phys; 2022 Nov; 23(11):e13758. PubMed ID: 36107021
    [Abstract] [Full Text] [Related]

  • 2. Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model.
    Conte GM, Weston AD, Vogelsang DC, Philbrick KA, Cai JC, Barbera M, Sanvito F, Lachance DH, Jenkins RB, Tobin WO, Eckel-Passow JE, Erickson BJ.
    Radiology; 2021 May; 299(2):313-323. PubMed ID: 33687284
    [No Abstract] [Full Text] [Related]

  • 3. MRI super-resolution using similarity distance and multi-scale receptive field based feature fusion GAN and pre-trained slice interpolation network.
    U N, P M A.
    Magn Reson Imaging; 2024 Jul; 110():195-209. PubMed ID: 38653336
    [Abstract] [Full Text] [Related]

  • 4. Texture transformer super-resolution for low-dose computed tomography.
    Zhou S, Yu L, Jin M.
    Biomed Phys Eng Express; 2022 Nov 04; 8(6):. PubMed ID: 36301699
    [Abstract] [Full Text] [Related]

  • 5. Unsupervised arterial spin labeling image superresolution via multiscale generative adversarial network.
    Cui J, Gong K, Han P, Liu H, Li Q.
    Med Phys; 2022 Apr 04; 49(4):2373-2385. PubMed ID: 35048390
    [Abstract] [Full Text] [Related]

  • 6. DeepSeg: deep neural network framework for automatic brain tumor segmentation using magnetic resonance FLAIR images.
    Zeineldin RA, Karar ME, Coburger J, Wirtz CR, Burgert O.
    Int J Comput Assist Radiol Surg; 2020 Jun 04; 15(6):909-920. PubMed ID: 32372386
    [Abstract] [Full Text] [Related]

  • 7. Generative adversarial network-based super-resolution of diffusion-weighted imaging: Application to tumour radiomics in breast cancer.
    Fan M, Liu Z, Xu M, Wang S, Zeng T, Gao X, Li L.
    NMR Biomed; 2020 Aug 04; 33(8):e4345. PubMed ID: 32521567
    [Abstract] [Full Text] [Related]

  • 8. SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks.
    Zhang K, Hu H, Philbrick K, Conte GM, Sobek JD, Rouzrokh P, Erickson BJ.
    Tomography; 2022 Mar 24; 8(2):905-919. PubMed ID: 35448707
    [Abstract] [Full Text] [Related]

  • 9. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.
    Tong N, Gou S, Yang S, Cao M, Sheng K.
    Med Phys; 2019 Jun 24; 46(6):2669-2682. PubMed ID: 31002188
    [Abstract] [Full Text] [Related]

  • 10. A Generative Adversarial Network technique for high-quality super-resolution reconstruction of cardiac magnetic resonance images.
    Zhao M, Wei Y, Wong KKL.
    Magn Reson Imaging; 2022 Jan 24; 85():153-160. PubMed ID: 34699953
    [Abstract] [Full Text] [Related]

  • 11. An expert system for brain tumor detection: Fuzzy C-means with super resolution and convolutional neural network with extreme learning machine.
    Özyurt F, Sert E, Avcı D.
    Med Hypotheses; 2020 Jan 24; 134():109433. PubMed ID: 31634769
    [Abstract] [Full Text] [Related]

  • 12. Multi-Modal Brain Tumor Data Completion Based on Reconstruction Consistency Loss.
    Jiang Y, Zhang S, Chi J.
    J Digit Imaging; 2023 Aug 24; 36(4):1794-1807. PubMed ID: 36856903
    [Abstract] [Full Text] [Related]

  • 13. A novel GAN-based three-axis mutually supervised super-resolution reconstruction method for rectal cancer MR image.
    Zhang H, Yang X, Cui Y, Wang Q, Zhao J, Li D.
    Comput Methods Programs Biomed; 2024 Dec 24; 257():108426. PubMed ID: 39368440
    [Abstract] [Full Text] [Related]

  • 14. Self-attention-based generative adversarial network optimized with color harmony algorithm for brain tumor classification.
    S SP, A S, T K, S D.
    Electromagn Biol Med; 2024 Apr 02; 43(1-2):31-45. PubMed ID: 38369844
    [Abstract] [Full Text] [Related]

  • 15. High-fidelity fast volumetric brain MRI using synergistic wave-controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN).
    Li Z, Tian Q, Ngamsombat C, Cartmell S, Conklin J, Filho ALMG, Lo WC, Wang G, Ying K, Setsompop K, Fan Q, Bilgic B, Cauley S, Huang SY.
    Med Phys; 2022 Feb 02; 49(2):1000-1014. PubMed ID: 34961944
    [Abstract] [Full Text] [Related]

  • 16. Generative adversarial network-based post-processed image super-resolution technology for accelerating brain MRI: comparison with compressed sensing.
    Ueki W, Nishii T, Umehara K, Ota J, Higuchi S, Ohta Y, Nagai Y, Murakawa K, Ishida T, Fukuda T.
    Acta Radiol; 2023 Jan 02; 64(1):336-345. PubMed ID: 35118883
    [Abstract] [Full Text] [Related]

  • 17. 3D MRI Reconstruction Based on 2D Generative Adversarial Network Super-Resolution.
    Zhang H, Shinomiya Y, Yoshida S.
    Sensors (Basel); 2021 Apr 23; 21(9):. PubMed ID: 33922811
    [Abstract] [Full Text] [Related]

  • 18. MRI super-resolution via realistic downsampling with adversarial learning.
    Huang B, Xiao H, Liu W, Zhang Y, Wu H, Wang W, Yang Y, Yang Y, Miller GW, Li T, Cai J.
    Phys Med Biol; 2021 Oct 05; 66(20):. PubMed ID: 34474407
    [Abstract] [Full Text] [Related]

  • 19. Handling Missing MRI Data in Brain Tumors Classification Tasks: Usage of Synthetic Images vs. Duplicate Images and Empty Images.
    Moshe YH, Buchsweiler Y, Teicher M, Artzi M.
    J Magn Reson Imaging; 2024 Aug 05; 60(2):561-573. PubMed ID: 37864370
    [Abstract] [Full Text] [Related]

  • 20. A new approach for brain tumor diagnosis system: Single image super resolution based maximum fuzzy entropy segmentation and convolutional neural network.
    Sert E, Özyurt F, Doğantekin A.
    Med Hypotheses; 2019 Dec 05; 133():109413. PubMed ID: 31586812
    [Abstract] [Full Text] [Related]

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