BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

153 related articles for article (PubMed ID: 29065648)

  • 1. Semiautomatic Segmentation of Glioma on Mobile Devices.
    Wu YP; Lin YS; Wu WG; Yang C; Gu JQ; Bai Y; Wang MY
    J Healthc Eng; 2017; 2017():8054939. PubMed ID: 29065648
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Brain tumor segmentation approach based on the extreme learning machine and significantly fast and robust fuzzy C-means clustering algorithms running on Raspberry Pi hardware.
    Şişik F; Sert E
    Med Hypotheses; 2020 Mar; 136():109507. PubMed ID: 31812927
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling.
    Deng M; Yu R; Wang L; Shi F; Yap PT; Shen D;
    Med Phys; 2016 Dec; 43(12):6588-6597. PubMed ID: 28054724
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated glioma detection and segmentation using graphical models.
    Zhao Z; Yang G; Lin Y; Pang H; Wang M
    PLoS One; 2018; 13(8):e0200745. PubMed ID: 30130371
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Fusion based Glioma brain tumor detection and segmentation using ANFIS classification.
    Selvapandian A; Manivannan K
    Comput Methods Programs Biomed; 2018 Nov; 166():33-38. PubMed ID: 30415716
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Automatic segmentation of multimodal brain tumor images based on classification of super-voxels.
    Kadkhodaei M; Samavi S; Karimi N; Mohaghegh H; Soroushmehr SM; Ward K; All A; Najarian K
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():5945-5948. PubMed ID: 28269606
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy.
    Ranjith G; Parvathy R; Vikas V; Chandrasekharan K; Nair S
    Neuroradiol J; 2015 Apr; 28(2):106-11. PubMed ID: 25923676
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned.
    Abd-Ellah MK; Awad AI; Khalaf AAM; Hamed HFA
    Magn Reson Imaging; 2019 Sep; 61():300-318. PubMed ID: 31173851
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: from atlas to dose-volume histograms.
    Conson M; Cella L; Pacelli R; Comerci M; Liuzzi R; Salvatore M; Quarantelli M
    Radiother Oncol; 2014 Sep; 112(3):326-31. PubMed ID: 25012642
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Automatic MRI 2D brain segmentation using graph searching technique.
    Pedoia V; Binaghi E
    Int J Numer Method Biomed Eng; 2013 Sep; 29(9):887-904. PubMed ID: 23757180
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Intraoperative tumor segmentation and volume measurement in MRI-guided glioma surgery for tumor resection rate control.
    Hata N; Muragaki Y; Inomata T; Maruyama T; Iseki H; Hori T; Dohi T
    Acad Radiol; 2005 Jan; 12(1):116-22. PubMed ID: 15691732
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Fuzzy local Gaussian mixture model for brain MR image segmentation.
    Ji Z; Xia Y; Sun Q; Chen Q; Xia D; Feng DD
    IEEE Trans Inf Technol Biomed; 2012 May; 16(3):339-47. PubMed ID: 22287250
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.
    Dolz J; Laprie A; Ken S; Leroy HA; Reyns N; Massoptier L; Vermandel M
    Int J Comput Assist Radiol Surg; 2016 Jan; 11(1):43-51. PubMed ID: 26206715
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.
    Sauwen N; Acou M; Van Cauter S; Sima DM; Veraart J; Maes F; Himmelreich U; Achten E; Van Huffel S
    Neuroimage Clin; 2016; 12():753-764. PubMed ID: 27812502
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Brain tumor target volume determination for radiation treatment planning through automated MRI segmentation.
    Mazzara GP; Velthuizen RP; Pearlman JL; Greenberg HM; Wagner H
    Int J Radiat Oncol Biol Phys; 2004 May; 59(1):300-12. PubMed ID: 15093927
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.
    Sauwen N; Acou M; Sima DM; Veraart J; Maes F; Himmelreich U; Achten E; Huffel SV
    BMC Med Imaging; 2017 May; 17(1):29. PubMed ID: 28472943
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A segmentation of brain MRI images utilizing intensity and contextual information by Markov random field.
    Chen M; Yan Q; Qin M
    Comput Assist Surg (Abingdon); 2017 Dec; 22(sup1):200-211. PubMed ID: 29072503
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Efficient Segmentation of Brain Tumor Using FL-SNM with a Metaheuristic Approach to Optimization.
    Natarajan A; Kumarasamy S
    J Med Syst; 2019 Jan; 43(2):25. PubMed ID: 30604101
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Robust generative asymmetric GMM for brain MR image segmentation.
    Ji Z; Xia Y; Zheng Y
    Comput Methods Programs Biomed; 2017 Nov; 151():123-138. PubMed ID: 28946994
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.