BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

274 related articles for article (PubMed ID: 23464305)

  • 21. Resolution enhancement of lung 4D-CT data using multiscale interphase iterative nonlocal means.
    Zhang Y; Yap PT; Wu G; Feng Q; Lian J; Chen W; Shen D
    Med Phys; 2013 May; 40(5):051916. PubMed ID: 23635286
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Lung motion estimation by robust point matching and spatiotemporal tracking for 4D CT.
    Yi J; Yang H; Yang X; Chen G
    Comput Biol Med; 2016 Nov; 78():107-119. PubMed ID: 27684323
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Lung Respiratory Motion Estimation Based on Fast Kalman Filtering and 4D CT Image Registration.
    Xue P; Fu Y; Ji H; Cui W; Dong E
    IEEE J Biomed Health Inform; 2021 Jun; 25(6):2007-2017. PubMed ID: 33044936
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Dosimetric evaluation of 4D-CBCT reconstructed by Simultaneous Motion Estimation and Image Reconstruction (SMEIR) for carbon ion therapy of lung cancer.
    Shrestha D; Tsai MY; Qin N; Zhang Y; Jia X; Wang J
    Med Phys; 2019 Sep; 46(9):4087-4094. PubMed ID: 31299097
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction.
    Fang S; Wang H; Liu Y; Zhang M; Yang W; Feng Q; Chen W; Zhang Y
    Phys Med Biol; 2017 Oct; 62(20):7925-7937. PubMed ID: 28872050
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Estimation of motion fields by non-linear registration for local lung motion analysis in 4D CT image data.
    Werner R; Ehrhardt J; Schmidt-Richberg A; Heiss A; Handels H
    Int J Comput Assist Radiol Surg; 2010 Nov; 5(6):595-605. PubMed ID: 20428958
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Segmentation and tracking of lung nodules via graph-cuts incorporating shape prior and motion from 4D CT.
    Cha J; Farhangi MM; Dunlap N; Amini AA
    Med Phys; 2018 Jan; 45(1):297-306. PubMed ID: 29164630
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Estimating 4D-CBCT from prior information and extremely limited angle projections using structural PCA and weighted free-form deformation for lung radiotherapy.
    Harris W; Zhang Y; Yin FF; Ren L
    Med Phys; 2017 Mar; 44(3):1089-1104. PubMed ID: 28079267
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Four-dimensional radiotherapy planning for DMLC-based respiratory motion tracking.
    Keall PJ; Joshi S; Vedam SS; Siebers JV; Kini VR; Mohan R
    Med Phys; 2005 Apr; 32(4):942-51. PubMed ID: 15895577
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Use of lung treatment plans to evaluate DIR algorithms.
    Jurkovic IA; Stathakis S; Li Y; Patel A; Vincent J; Papanikolaou N; Mavroidis P
    Australas Phys Eng Sci Med; 2018 Dec; 41(4):837-845. PubMed ID: 30144019
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Reconstruction of a time-averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registration.
    Wolthaus JW; Sonke JJ; van Herk M; Damen EM
    Med Phys; 2008 Sep; 35(9):3998-4011. PubMed ID: 18841851
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Low-dose 4D cone-beam CT via joint spatiotemporal regularization of tensor framelet and nonlocal total variation.
    Han H; Gao H; Xing L
    Phys Med Biol; 2017 Jul; 62(16):6408-6427. PubMed ID: 28726684
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm.
    Yi J; Yang X; Chen G; Li YR
    Med Phys; 2015 Oct; 42(10):5616-32. PubMed ID: 26429236
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Self-contained deep learning-based boosting of 4D cone-beam CT reconstruction.
    Madesta F; Sentker T; Gauer T; Werner R
    Med Phys; 2020 Nov; 47(11):5619-5631. PubMed ID: 33063329
    [TBL] [Abstract][Full Text] [Related]  

  • 35. A novel four-dimensional radiotherapy planning strategy from a tumor-tracking beam's eye view.
    Li G; Cohen P; Xie H; Low D; Li D; Rimner A
    Phys Med Biol; 2012 Nov; 57(22):7579-98. PubMed ID: 23103415
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A novel fast helical 4D-CT acquisition technique to generate low-noise sorting artifact-free images at user-selected breathing phases.
    Thomas D; Lamb J; White B; Jani S; Gaudio S; Lee P; Ruan D; McNitt-Gray M; Low D
    Int J Radiat Oncol Biol Phys; 2014 May; 89(1):191-8. PubMed ID: 24613815
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.
    Marx M; Ehrhardt J; Werner R; Schlemmer HP; Handels H
    Int J Comput Assist Radiol Surg; 2014 May; 9(3):401-9. PubMed ID: 24323401
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Hierarchical patch-based sparse representation--a new approach for resolution enhancement of 4D-CT lung data.
    Zhang Y; Wu G; Yap PT; Feng Q; Lian J; Chen W; Shen D
    IEEE Trans Med Imaging; 2012 Nov; 31(11):1993-2005. PubMed ID: 22692897
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Motion vector field phase-to-amplitude resampling for 4D motion-compensated cone-beam CT.
    Sauppe S; Kuhm J; Brehm M; Paysan P; Seghers D; Kachelrieß M
    Phys Med Biol; 2018 Feb; 63(3):035032. PubMed ID: 29235989
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Directional sinogram interpolation for motion weighted 4D cone-beam CT reconstruction.
    Zhang H; Kruis M; Sonke JJ
    Phys Med Biol; 2017 Mar; 62(6):2254-2275. PubMed ID: 28140361
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 14.