BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

125 related articles for article (PubMed ID: 37499682)

  • 1. Performance assessment of variant UNet-based deep-learning dose engines for MR-Linac-based prostate IMRT plans.
    Tseng W; Liu H; Yang Y; Liu C; Furutani K; Beltran C; Lu B
    Phys Med Biol; 2023 Aug; 68(17):. PubMed ID: 37499682
    [No Abstract]   [Full Text] [Related]  

  • 2. An ultra-fast deep-learning-based dose engine for prostate VMAT via knowledge distillation framework with limited patient data.
    Tseng W; Liu H; Yang Y; Liu C; Lu B
    Phys Med Biol; 2022 Dec; 68(1):. PubMed ID: 36533689
    [No Abstract]   [Full Text] [Related]  

  • 3. DeepDose: Towards a fast dose calculation engine for radiation therapy using deep learning.
    Kontaxis C; Bol GH; Lagendijk JJW; Raaymakers BW
    Phys Med Biol; 2020 Apr; 65(7):075013. PubMed ID: 32053803
    [TBL] [Abstract][Full Text] [Related]  

  • 4. TransDose: a transformer-based UNet model for fast and accurate dose calculation for MR-LINACs.
    Xiao F; Cai J; Zhou X; Zhou L; Song T; Li Y
    Phys Med Biol; 2022 Jun; 67(12):. PubMed ID: 35613559
    [No Abstract]   [Full Text] [Related]  

  • 5. Development and clinical application of a GPU-based Monte Carlo dose verification module and software for 1.5 T MR-LINAC.
    Cheng B; Xu Y; Li S; Ren Q; Pei X; Men K; Dai J; Xu XG
    Med Phys; 2023 May; 50(5):3172-3183. PubMed ID: 36862110
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Dosimetric comparison of MR-linac-based IMRT and conventional VMAT treatment plans for prostate cancer.
    Da Silva Mendes V; Nierer L; Li M; Corradini S; Reiner M; Kamp F; Niyazi M; Kurz C; Landry G; Belka C
    Radiat Oncol; 2021 Jul; 16(1):133. PubMed ID: 34289868
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Technical Note: A feasibility study on deep learning-based radiotherapy dose calculation.
    Xing Y; Nguyen D; Lu W; Yang M; Jiang S
    Med Phys; 2020 Feb; 47(2):753-758. PubMed ID: 31808948
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations.
    Tian Z; Li Y; Folkerts M; Shi F; Jiang SB; Jia X
    Phys Med Biol; 2015 Oct; 60(20):7941-67. PubMed ID: 26418216
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Robust deep learning-based forward dose calculations for VMAT on the 1.5T MR-linac.
    Tsekas G; Bol GH; Raaymakers BW
    Phys Med Biol; 2022 Nov; 67(22):. PubMed ID: 36198322
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The commissioning and validation of Monaco treatment planning system on an Elekta VersaHD linear accelerator.
    Snyder JE; Hyer DE; Flynn RT; Boczkowski A; Wang D
    J Appl Clin Med Phys; 2019 Jan; 20(1):184-193. PubMed ID: 30525308
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Extension and validation of a GPU-Monte Carlo dose engine gDPM for 1.5 T MR-LINAC online independent dose verification.
    Li Y; Ding S; Wang B; Liu H; Huang X; Song T
    Med Phys; 2021 Oct; 48(10):6174-6183. PubMed ID: 34387872
    [TBL] [Abstract][Full Text] [Related]  

  • 12. DeepDose: a robust deep learning-based dose engine for abdominal tumours in a 1.5 T MRI radiotherapy system.
    Tsekas G; Bol GH; Raaymakers BW; Kontaxis C
    Phys Med Biol; 2021 Mar; 66(6):065017. PubMed ID: 33545708
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Generalisation of radiotherapy dose calculation for Monte Carlo algorithm combined with 3D Swin-Unet: a multi-institutional IMRT evaluation.
    Zhang B; Zhuang Y; Li Y; Chen L; Liu X; Liu Z; Wang X; Zhu J
    Phys Med Biol; 2023 Oct; 68(21):. PubMed ID: 37827160
    [No Abstract]   [Full Text] [Related]  

  • 14. Cross-engine transformation-based fast dose calculation for MRI-Linac online treatment planning.
    Song T; Zhou L; Li Y
    Med Phys; 2023 Apr; 50(4):2429-2437. PubMed ID: 36346038
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development and validation of a 1.5 T MR-Linac full accelerator head and cryostat model for Monte Carlo dose simulations.
    Friedel M; Nachbar M; Mönnich D; Dohm O; Thorwarth D
    Med Phys; 2019 Nov; 46(11):5304-5313. PubMed ID: 31532829
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MRI-based IMRT planning for MR-linac: comparison between CT- and MRI-based plans for pancreatic and prostate cancers.
    Prior P; Chen X; Botros M; Paulson ES; Lawton C; Erickson B; Li XA
    Phys Med Biol; 2016 May; 61(10):3819-42. PubMed ID: 27089554
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Moving GPU-OpenCL-based Monte Carlo dose calculation toward clinical use: Automatic beam commissioning and source sampling for treatment plan dose calculation.
    Tian Z; Li Y; Hassan-Rezaeian N; Jiang SB; Jia X
    J Appl Clin Med Phys; 2017 Mar; 18(2):69-84. PubMed ID: 28300376
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of treatment plan quality among MRI-based IMRT with a linac, MRI-based IMRT with tri-Co-60 sources, and VMAT for spine SABR.
    Choi CH; Kim JH; Kim JI; Park JM
    PLoS One; 2019; 14(7):e0220039. PubMed ID: 31329641
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Comparison of Intensity Modulated Radiotherapy Treatment Plans Between 1.5T MR-Linac and Conventional Linac.
    Ding S; Li Y; Liu H; Li R; Wang B; Zhang J; Chen Y; Huang X
    Technol Cancer Res Treat; 2021; 20():1533033820985871. PubMed ID: 33472549
    [TBL] [Abstract][Full Text] [Related]  

  • 20. First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer.
    Bijman R; Rossi L; Janssen T; de Ruiter P; Carbaat C; van Triest B; Breedveld S; Sonke JJ; Heijmen B
    Acta Oncol; 2020 Aug; 59(8):926-932. PubMed ID: 32436450
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 7.