BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

466 related articles for article (PubMed ID: 35897425)

  • 21. Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer.
    Hoang Duc AK; Eminowicz G; Mendes R; Wong SL; McClelland J; Modat M; Cardoso MJ; Mendelson AF; Veiga C; Kadir T; D'Souza D; Ourselin S
    Med Phys; 2015 Sep; 42(9):5027-34. PubMed ID: 26328953
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region.
    Kieselmann JP; Kamerling CP; Burgos N; Menten MJ; Fuller CD; Nill S; Cardoso MJ; Oelfke U
    Phys Med Biol; 2018 Jul; 63(14):145007. PubMed ID: 29882749
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Evaluating the clinical acceptability of deep learning contours of prostate and organs-at-risk in an automated prostate treatment planning process.
    Duan J; Bernard M; Downes L; Willows B; Feng X; Mourad WF; St Clair W; Chen Q
    Med Phys; 2022 Apr; 49(4):2570-2581. PubMed ID: 35147216
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Transfer learning for auto-segmentation of 17 organs-at-risk in the head and neck: Bridging the gap between institutional and public datasets.
    Clark B; Hardcastle N; Johnston LA; Korte J
    Med Phys; 2024 Feb; ():. PubMed ID: 38376454
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Head and neck multi-organ auto-segmentation on CT images aided by synthetic MRI.
    Liu Y; Lei Y; Fu Y; Wang T; Zhou J; Jiang X; McDonald M; Beitler JJ; Curran WJ; Liu T; Yang X
    Med Phys; 2020 Sep; 47(9):4294-4302. PubMed ID: 32648602
    [TBL] [Abstract][Full Text] [Related]  

  • 26. General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvis.
    Amjad A; Xu J; Thill D; Lawton C; Hall W; Awan MJ; Shukla M; Erickson BA; Li XA
    Med Phys; 2022 Mar; 49(3):1686-1700. PubMed ID: 35094390
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.
    Chen X; Sun S; Bai N; Han K; Liu Q; Yao S; Tang H; Zhang C; Lu Z; Huang Q; Zhao G; Xu Y; Chen T; Xie X; Liu Y
    Radiother Oncol; 2021 Jul; 160():175-184. PubMed ID: 33961914
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Auto-segmentation of important centers of growth in the pediatric skeleton to consider during radiation therapy based on deep learning.
    Qiu W; Zhang W; Ma X; Kong Y; Shi P; Fu M; Wang D; Hu M; Zhou X; Dong Q; Zhou Q; Zhu J
    Med Phys; 2023 Jan; 50(1):284-296. PubMed ID: 36047281
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Head-and-neck organs-at-risk auto-delineation using dual pyramid networks for CBCT-guided adaptive radiotherapy.
    Dai X; Lei Y; Wang T; Dhabaan AH; McDonald M; Beitler JJ; Curran WJ; Zhou J; Liu T; Yang X
    Phys Med Biol; 2021 Feb; 66(4):045021. PubMed ID: 33412527
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Validation of a Magnetic Resonance Imaging-based Auto-contouring Software Tool for Gross Tumour Delineation in Head and Neck Cancer Radiotherapy Planning.
    Doshi T; Wilson C; Paterson C; Lamb C; James A; MacKenzie K; Soraghan J; Petropoulakis L; Di Caterina G; Grose D
    Clin Oncol (R Coll Radiol); 2017 Jan; 29(1):60-67. PubMed ID: 27780693
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Evaluating Automatic Segmentation for Swallowing-Related Organs for Head and Neck Cancer.
    Li Y; Rao S; Chen W; Azghadi SF; Nguyen KNB; Moran A; Usera BM; Dyer BA; Shang L; Chen Q; Rong Y
    Technol Cancer Res Treat; 2022; 21():15330338221105724. PubMed ID: 35790457
    [No Abstract]   [Full Text] [Related]  

  • 32. Weaving attention U-net: A novel hybrid CNN and attention-based method for organs-at-risk segmentation in head and neck CT images.
    Zhang Z; Zhao T; Gay H; Zhang W; Sun B
    Med Phys; 2021 Nov; 48(11):7052-7062. PubMed ID: 34655077
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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; 46(6):2669-2682. PubMed ID: 31002188
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Initial Evaluation of a Novel Cone-Beam CT-Based Semi-Automated Online Adaptive Radiotherapy System for Head and Neck Cancer Treatment - A Timing and Automation Quality Study.
    Yoon SW; Lin H; Alonso-Basanta M; Anderson N; Apinorasethkul O; Cooper K; Dong L; Kempsey B; Marcel J; Metz J; Scheuermann R; Li T
    Cureus; 2020 Aug; 12(8):e9660. PubMed ID: 32923257
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Segmentation of organs-at-risk in cervical cancer CT images with a convolutional neural network.
    Liu Z; Liu X; Xiao B; Wang S; Miao Z; Sun Y; Zhang F
    Phys Med; 2020 Jan; 69():184-191. PubMed ID: 31918371
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Evaluation of an automatic segmentation algorithm for definition of head and neck organs at risk.
    Thomson D; Boylan C; Liptrot T; Aitkenhead A; Lee L; Yap B; Sykes A; Rowbottom C; Slevin N
    Radiat Oncol; 2014 Aug; 9():173. PubMed ID: 25086641
    [TBL] [Abstract][Full Text] [Related]  

  • 37. vOARiability: Interobserver and intermodality variability analysis in OAR contouring from head and neck CT and MR images.
    Podobnik G; Ibragimov B; Peterlin P; Strojan P; Vrtovec T
    Med Phys; 2024 Mar; 51(3):2175-2186. PubMed ID: 38230752
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Improved accuracy of auto-segmentation of organs at risk in radiotherapy planning for nasopharyngeal carcinoma based on fully convolutional neural network deep learning.
    Peng Y; Liu Y; Shen G; Chen Z; Chen M; Miao J; Zhao C; Deng J; Qi Z; Deng X
    Oral Oncol; 2023 Jan; 136():106261. PubMed ID: 36446186
    [TBL] [Abstract][Full Text] [Related]  

  • 39. [Not Available].
    Zhang L; Liu Z; Zhang L; Wu Z; Yu X; Holmes J; Feng H; Dai H; Li X; Li Q; Wong WW; Vora SA; Zhu D; Liu T; Liu W
    Med Phys; 2024 Mar; 51(3):2187-2199. PubMed ID: 38319676
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging.
    Korte JC; Hardcastle N; Ng SP; Clark B; Kron T; Jackson P
    Med Phys; 2021 Dec; 48(12):7757-7772. PubMed ID: 34676555
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 24.