These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

191 related articles for article (PubMed ID: 31456678)

  • 1. Automatic Brain Tumor Segmentation Based on Cascaded Convolutional Neural Networks With Uncertainty Estimation.
    Wang G; Li W; Ourselin S; Vercauteren T
    Front Comput Neurosci; 2019; 13():56. PubMed ID: 31456678
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Asymmetric Ensemble of Asymmetric U-Net Models for Brain Tumor Segmentation With Uncertainty Estimation.
    Rosas-Gonzalez S; Birgui-Sekou T; Hidane M; Zemmoura I; Tauber C
    Front Neurol; 2021; 12():609646. PubMed ID: 34659077
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks.
    Wang G; Li W; Aertsen M; Deprest J; Ourselin S; Vercauteren T
    Neurocomputing (Amst); 2019 Sep; 335():34-45. PubMed ID: 31595105
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated glioma grading on conventional MRI images using deep convolutional neural networks.
    Zhuge Y; Ning H; Mathen P; Cheng JY; Krauze AV; Camphausen K; Miller RW
    Med Phys; 2020 Jul; 47(7):3044-3053. PubMed ID: 32277478
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Brain tumor segmentation using holistically nested neural networks in MRI images.
    Zhuge Y; Krauze AV; Ning H; Cheng JY; Arora BC; Camphausen K; Miller RW
    Med Phys; 2017 Oct; 44(10):5234-5243. PubMed ID: 28736864
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fully automated segmentation of brain tumor from multiparametric MRI using 3D context deep supervised U-Net.
    Lin M; Momin S; Lei Y; Wang H; Curran WJ; Liu T; Yang X
    Med Phys; 2021 Aug; 48(8):4365-4374. PubMed ID: 34101845
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Automatic Segmentation of MRI of Brain Tumor Using Deep Convolutional Network.
    Zhou R; Hu S; Ma B; Ma B
    Biomed Res Int; 2022; 2022():4247631. PubMed ID: 35757482
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A systematic evaluation of learning rate policies in training CNNs for brain tumor segmentation.
    Bukhari ST; Mohy-Ud-Din H
    Phys Med Biol; 2021 May; 66(10):. PubMed ID: 33545703
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multiscale Local Enhancement Deep Convolutional Networks for the Automated 3D Segmentation of Gross Tumor Volumes in Nasopharyngeal Carcinoma: A Multi-Institutional Dataset Study.
    Yang G; Dai Z; Zhang Y; Zhu L; Tan J; Chen Z; Zhang B; Cai C; He Q; Li F; Wang X; Yang W
    Front Oncol; 2022; 12():827991. PubMed ID: 35387126
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Fusing 2D and 3D convolutional neural networks for the segmentation of aorta and coronary arteries from CT images.
    Gu L; Cai XC
    Artif Intell Med; 2021 Nov; 121():102189. PubMed ID: 34763804
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 3D convolutional neural networks for tumor segmentation using long-range 2D context.
    Mlynarski P; Delingette H; Criminisi A; Ayache N
    Comput Med Imaging Graph; 2019 Apr; 73():60-72. PubMed ID: 30889541
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images.
    Naceur MB; Saouli R; Akil M; Kachouri R
    Comput Methods Programs Biomed; 2018 Nov; 166():39-49. PubMed ID: 30415717
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy.
    Ben Naceur M; Akil M; Saouli R; Kachouri R
    Med Image Anal; 2020 Jul; 63():101692. PubMed ID: 32417714
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images.
    Ren X; Xiang L; Nie D; Shao Y; Zhang H; Shen D; Wang Q
    Med Phys; 2018 May; 45(5):2063-2075. PubMed ID: 29480928
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.
    Cui S; Mao L; Jiang J; Liu C; Xiong S
    J Healthc Eng; 2018; 2018():4940593. PubMed ID: 29755716
    [TBL] [Abstract][Full Text] [Related]  

  • 17. SwinBTS: A Method for 3D Multimodal Brain Tumor Segmentation Using Swin Transformer.
    Jiang Y; Zhang Y; Lin X; Dong J; Cheng T; Liang J
    Brain Sci; 2022 Jun; 12(6):. PubMed ID: 35741682
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
    Burton W; Myers C; Rullkoetter P
    Comput Methods Programs Biomed; 2020 Jun; 189():105328. PubMed ID: 31958580
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Application of deep learning for automatic segmentation of brain tumors on magnetic resonance imaging: a heuristic approach in the clinical scenario.
    Di Ieva A; Russo C; Liu S; Jian A; Bai MY; Qian Y; Magnussen JS
    Neuroradiology; 2021 Aug; 63(8):1253-1262. PubMed ID: 33501512
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Memory-efficient Deep Framework for Multi-Modal MRI-based Brain Tumor Segmentation.
    Hashemi N; Masoudnia S; Nejad A; Nazem-Zadeh MR
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3749-3752. PubMed ID: 36086352
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.