BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

151 related articles for article (PubMed ID: 31529506)

  • 1. Technical Note: Machine learning approaches for range and dose verification in proton therapy using proton-induced positron emitters.
    Li Z; Wang Y; Yu Y; Fan K; Xing L; Peng H
    Med Phys; 2019 Dec; 46(12):5748-5757. PubMed ID: 31529506
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Range and dose verification in proton therapy using proton-induced positron emitters and recurrent neural networks (RNNs).
    Liu C; Li Z; Hu W; Xing L; Peng H
    Phys Med Biol; 2019 Sep; 64(17):175009. PubMed ID: 31342940
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A machine learning framework with anatomical prior for online dose verification using positron emitters and PET in proton therapy.
    Hu Z; Li G; Zhang X; Ye K; Lu J; Peng H
    Phys Med Biol; 2020 Sep; 65(18):185003. PubMed ID: 32460246
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Feasibility study of patient-specific dose verification in proton therapy utilizing positron emission tomography (PET) and generative adversarial network (GAN).
    Ma S; Hu Z; Ye K; Zhang X; Wang Y; Peng H
    Med Phys; 2020 Oct; 47(10):5194-5208. PubMed ID: 32772377
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Further investigation of 3D dose verification in proton therapy utilizing acoustic signal, wavelet decomposition and machine learning.
    Yao S; Hu Z; Xie Q; Yang Y; Peng H
    Biomed Phys Eng Express; 2021 Nov; 8(1):. PubMed ID: 34768245
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning based oxygen and carbon concentration derivation using dual-energy CT for PET-based dose verification in proton therapy.
    Liu Y; Zhou L; Peng H
    Med Phys; 2022 May; 49(5):3347-3360. PubMed ID: 35246842
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Technical note: Implementing MRI/CT-based elemental concentration data to Monte Carlo simulation for yielding positron emitters in proton therapy.
    Saito M; Matsumoto R
    Med Phys; 2024 Apr; 51(4):2861-2870. PubMed ID: 38116829
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Feasibility study of range verification based on proton-induced acoustic signals and recurrent neural network.
    Yao S; Hu Z; Zhang X; Lou E; Liang Z; Wang Y; Peng H
    Phys Med Biol; 2020 Nov; 65(21):215017. PubMed ID: 32726760
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Benchmarking a GATE/Geant4 Monte Carlo model for proton beams in magnetic fields.
    Padilla-Cabal F; Alejandro Fragoso J; Franz Resch A; Georg D; Fuchs H
    Med Phys; 2020 Jan; 47(1):223-233. PubMed ID: 31661559
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Evaluation of GATE-RTion (GATE/Geant4) Monte Carlo simulation settings for proton pencil beam scanning quality assurance.
    Winterhalter C; Taylor M; Boersma D; Elia A; Guatelli S; Mackay R; Kirkby K; Maigne L; Ivanchenko V; Resch AF; Sarrut D; Sitch P; Vidal M; Grevillot L; Aitkenhead A
    Med Phys; 2020 Nov; 47(11):5817-5828. PubMed ID: 32967037
    [TBL] [Abstract][Full Text] [Related]  

  • 11. ML-EM algorithm for dose estimation using PET in proton therapy.
    Masuda T; Nishio T; Kataoka J; Arimoto M; Sano A; Karasawa K
    Phys Med Biol; 2019 Sep; 64(17):175011. PubMed ID: 31307027
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A machine learning-based framework for delivery error prediction in proton pencil beam scanning using irradiation log-files.
    Maes D; Bowen SR; Regmi R; Bloch C; Wong T; Rosenfeld A; Saini J
    Phys Med; 2020 Oct; 78():179-186. PubMed ID: 33038643
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Extension of the ML-EM algorithm for dose estimation using PET in proton therapy: application to an inhomogeneous target.
    Masuda T; Nishio T; Sano A; Karasawa K
    Phys Med Biol; 2020 Sep; 65(18):185001. PubMed ID: 32485687
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An artificial neural network based approach for predicting the proton beam spot dosimetric characteristics of a pencil beam scanning technique.
    Ranjith CP; Krishnan M; Raveendran V; Chaudhari L; Laskar S
    Biomed Phys Eng Express; 2024 Apr; 10(3):. PubMed ID: 38652667
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Use of short-lived positron emitters for in-beam and real-time β
    Bongrand A; Busato E; Force P; Martin F; Montarou G
    Phys Med; 2020 Jan; 69():248-255. PubMed ID: 31918377
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Experimental validation of the TOPAS Monte Carlo system for passive scattering proton therapy.
    Testa M; Schümann J; Lu HM; Shin J; Faddegon B; Perl J; Paganetti H
    Med Phys; 2013 Dec; 40(12):121719. PubMed ID: 24320505
    [TBL] [Abstract][Full Text] [Related]  

  • 17. TPS(PET)-A TPS-based approach for in vivo dose verification with PET in proton therapy.
    Frey K; Bauer J; Unholtz D; Kurz C; Krämer M; Bortfeld T; Parodi K
    Phys Med Biol; 2014 Jan; 59(1):1-21. PubMed ID: 24323977
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Toward a new treatment planning approach accounting for in vivo proton range verification.
    Tian L; Landry G; Dedes G; Kamp F; Pinto M; Niepel K; Belka C; Parodi K
    Phys Med Biol; 2018 Oct; 63(21):215025. PubMed ID: 30375361
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Technical Note: Experimental verification of magnetic field-induced beam deflection and Bragg peak displacement for MR-integrated proton therapy.
    Schellhammer SM; Gantz S; Lühr A; Oborn BM; Bussmann M; Hoffmann AL
    Med Phys; 2018 Jul; 45(7):3429-3434. PubMed ID: 29763970
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A pencil beam algorithm for magnetic resonance image-guided proton therapy.
    Padilla-Cabal F; Georg D; Fuchs H
    Med Phys; 2018 May; 45(5):2195-2204. PubMed ID: 29532490
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.