BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1540 related articles for article (PubMed ID: 31077390)

  • 1. Projection-domain scatter correction for cone beam computed tomography using a residual convolutional neural network.
    Nomura Y; Xu Q; Shirato H; Shimizu S; Xing L
    Med Phys; 2019 Jul; 46(7):3142-3155. PubMed ID: 31077390
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Combining scatter reduction and correction to improve image quality in cone-beam computed tomography (CBCT).
    Jin JY; Ren L; Liu Q; Kim J; Wen N; Guan H; Movsas B; Chetty IJ
    Med Phys; 2010 Nov; 37(11):5634-44. PubMed ID: 21158275
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A correlated sampling-based Monte Carlo simulation for fast CBCT iterative scatter correction.
    Qin P; Lin G; Li X; Piao Z; Huang S; Wu W; Qi M; Ma J; Zhou L; Xu Y
    Med Phys; 2023 Mar; 50(3):1466-1480. PubMed ID: 36323626
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder.
    van der Heyden B; Uray M; Fonseca GP; Huber P; Us D; Messner I; Law A; Parii A; Reisz N; Rinaldi I; Vilches Freixas G; Deutschmann H; Verhaegen F; Steininger P
    Phys Med Biol; 2020 Jul; 65(14):145002. PubMed ID: 32294626
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluation of CBCT scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy.
    Lalonde A; Winey B; Verburg J; Paganetti H; Sharp GC
    Phys Med Biol; 2020 Dec; 65(24):. PubMed ID: 32580174
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep learning for x-ray scatter correction in dedicated breast CT.
    Pautasso JJ; Caballo M; Mikerov M; Boone JM; Michielsen K; Sechopoulos I
    Med Phys; 2023 Apr; 50(4):2022-2036. PubMed ID: 36565012
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modified fast adaptive scatter kernel superposition (mfASKS) correction and its dosimetric impact on CBCT-based proton therapy dose calculation.
    Nomura Y; Xu Q; Peng H; Takao S; Shimizu S; Xing L; Shirato H
    Med Phys; 2020 Jan; 47(1):190-200. PubMed ID: 31661161
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A convolutional neural network for estimating cone-beam CT intensity deviations from virtual CT projections.
    Rusanov B; Ebert MA; Mukwada G; Hassan GM; Sabet M
    Phys Med Biol; 2021 Oct; 66(21):. PubMed ID: 34534979
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A model-based scatter artifacts correction for cone beam CT.
    Zhao W; Vernekohl D; Zhu J; Wang L; Xing L
    Med Phys; 2016 Apr; 43(4):1736. PubMed ID: 27036571
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Convolutional neural network enhancement of fast-scan low-dose cone-beam CT images for head and neck radiotherapy.
    Yuan N; Dyer B; Rao S; Chen Q; Benedict S; Shang L; Kang Y; Qi J; Rong Y
    Phys Med Biol; 2020 Jan; 65(3):035003. PubMed ID: 31842014
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Efficient scatter distribution estimation and correction in CBCT using concurrent Monte Carlo fitting.
    Bootsma GJ; Verhaegen F; Jaffray DA
    Med Phys; 2015 Jan; 42(1):54-68. PubMed ID: 25563247
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Multi-energy blended CBCT spectral imaging and scatter-decoupled material decomposition using a spectral modulator with flying focal spot (SMFFS).
    Deng Y; Zhou H; Wang Z; Wang AS; Gao H
    Med Phys; 2024 Apr; 51(4):2398-2412. PubMed ID: 38477717
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A deep learning approach to estimate x-ray scatter in digital breast tomosynthesis: From phantom models to clinical applications.
    Pinto MC; Mauter F; Michielsen K; Biniazan R; Kappler S; Sechopoulos I
    Med Phys; 2023 Aug; 50(8):4744-4757. PubMed ID: 37394837
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Shading correction for on-board cone-beam CT in radiation therapy using planning MDCT images.
    Niu T; Sun M; Star-Lack J; Gao H; Fan Q; Zhu L
    Med Phys; 2010 Oct; 37(10):5395-406. PubMed ID: 21089775
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Augmentation of CBCT Reconstructed From Under-Sampled Projections Using Deep Learning.
    Jiang Z; Chen Y; Zhang Y; Ge Y; Yin FF; Ren L
    IEEE Trans Med Imaging; 2019 Nov; 38(11):2705-2715. PubMed ID: 31021791
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Correction for patient table-induced scattered radiation in cone-beam computed tomography (CBCT).
    Sun M; Nagy T; Virshup G; Partain L; Oelhafen M; Star-Lack J
    Med Phys; 2011 Apr; 38(4):2058-73. PubMed ID: 21626939
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Image-based scatter correction for cone-beam CT using flip swin transformer U-shape network.
    Zhang X; Jiang Y; Luo C; Li D; Niu T; Yu G
    Med Phys; 2023 Aug; 50(8):5002-5019. PubMed ID: 36734321
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Dual-energy head cone-beam CT using a dual-layer flat-panel detector: Hybrid material decomposition and a feasibility study.
    Wang Z; Zhou H; Gu S; Xia Y; Liao H; Deng Y; Gao H
    Med Phys; 2023 Nov; 50(11):6762-6778. PubMed ID: 37675888
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Scatter correction based on adaptive photon path-based Monte Carlo simulation method in Multi-GPU platform.
    Zhang Y; Chen Y; Zhong A; Jia X; Wu S; Qi H; Zhou L; Xu Y
    Comput Methods Programs Biomed; 2020 Oct; 194():105487. PubMed ID: 32473514
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An unsupervised dual contrastive learning framework for scatter correction in cone-beam CT image.
    Wang T; Liu X; Dai J; Zhang C; He W; Liu L; Chan Y; He Y; Zhao H; Xie Y; Liang X
    Comput Biol Med; 2023 Oct; 165():107377. PubMed ID: 37651766
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 77.