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Journal Abstract Search

1463 related items for PubMed ID: 30887523

  • 1. A convolutional neural network algorithm for automatic segmentation of head and neck organs at risk using deep lifelong learning.
    Chan JW, Kearney V, Haaf S, Wu S, Bogdanov M, Reddick M, Dixit N, Sudhyadhom A, Chen J, Yom SS, Solberg TD.
    Med Phys; 2019 May; 46(5):2204-2213. PubMed ID: 30887523
    [Abstract] [Full Text] [Related]

  • 2. Attention-enabled 3D boosted convolutional neural networks for semantic CT segmentation using deep supervision.
    Kearney V, Chan JW, Wang T, Perry A, Yom SS, Solberg TD.
    Phys Med Biol; 2019 Jul 02; 64(13):135001. PubMed ID: 31181561
    [Abstract] [Full Text] [Related]

  • 3. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.
    Ibragimov B, Xing L.
    Med Phys; 2017 Feb 02; 44(2):547-557. PubMed ID: 28205307
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  • 4. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
    Zhu W, Huang Y, Zeng L, Chen X, Liu Y, Qian Z, Du N, Fan W, Xie X.
    Med Phys; 2019 Feb 02; 46(2):576-589. PubMed ID: 30480818
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  • 5. Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.
    Men K, Dai J, Li Y.
    Med Phys; 2017 Dec 02; 44(12):6377-6389. PubMed ID: 28963779
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  • 8. 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 02; 46(6):2669-2682. PubMed ID: 31002188
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  • 11. Deep convolutional neural network for segmentation of thoracic organs-at-risk using cropped 3D images.
    Feng X, Qing K, Tustison NJ, Meyer CH, Chen Q.
    Med Phys; 2019 May 02; 46(5):2169-2180. PubMed ID: 30830685
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  • 12. Deep-learning convolutional neural network: Inner and outer bladder wall segmentation in CT urography.
    Gordon MN, Hadjiiski LM, Cha KH, Samala RK, Chan HP, Cohan RH, Caoili EM.
    Med Phys; 2019 Feb 02; 46(2):634-648. PubMed ID: 30520055
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  • 13. A novel MRI segmentation method using CNN-based correction network for MRI-guided adaptive radiotherapy.
    Fu Y, Mazur TR, Wu X, Liu S, Chang X, Lu Y, Li HH, Kim H, Roach MC, Henke L, Yang D.
    Med Phys; 2018 Nov 02; 45(11):5129-5137. PubMed ID: 30269345
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  • 14. Artificial Intelligence Radiotherapy Planning: Automatic Segmentation of Human Organs in CT Images Based on a Modified Convolutional Neural Network.
    Shen G, Jin X, Sun C, Li Q.
    Front Public Health; 2022 Nov 02; 10():813135. PubMed ID: 35493368
    [Abstract] [Full Text] [Related]

  • 15. Deep learning with uncertainty estimation for automatic tumor segmentation in PET/CT of head and neck cancers: impact of model complexity, image processing and augmentation.
    Huynh BN, Groendahl AR, Tomic O, Liland KH, Knudtsen IS, Hoebers F, van Elmpt W, Dale E, Malinen E, Futsaether CM.
    Biomed Phys Eng Express; 2024 Aug 30; 10(5):. PubMed ID: 39127060
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  • 16. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
    Fu J, Yang Y, Singhrao K, Ruan D, Chu FI, Low DA, Lewis JH.
    Med Phys; 2019 Sep 30; 46(9):3788-3798. PubMed ID: 31220353
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  • 17. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.
    Xu M, Qi S, Yue Y, Teng Y, Xu L, Yao Y, Qian W.
    Biomed Eng Online; 2019 Jan 03; 18(1):2. PubMed ID: 30602393
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  • 18. 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 03; 48(12):7757-7772. PubMed ID: 34676555
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  • 19. 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 03; 136():106261. PubMed ID: 36446186
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  • 20. Technical Note: More accurate and efficient segmentation of organs-at-risk in radiotherapy with convolutional neural networks cascades.
    Men K, Geng H, Cheng C, Zhong H, Huang M, Fan Y, Plastaras JP, Lin A, Xiao Y.
    Med Phys; 2019 Jan 03; 46(1):286-292. PubMed ID: 30450825
    [Abstract] [Full Text] [Related]

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