BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 37977889)

  • 1. Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation.
    Bathla G; Dhruba DD; Liu Y; Le NH; Soni N; Zhang H; Mohan S; Roberts-Wolfe D; Rathore S; Sonka M; Priya S; Agarwal A
    Acad Radiol; 2024 May; 31(5):2041-2049. PubMed ID: 37977889
    [TBL] [Abstract][Full Text] [Related]  

  • 2. AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.
    Bathla G; Dhruba DD; Soni N; Liu Y; Larson NB; Kassmeyer BA; Mohan S; Roberts-Wolfe D; Rathore S; Le NH; Zhang H; Sonka M; Priya S
    J Neuroradiol; 2024 May; 51(3):258-264. PubMed ID: 37652263
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Development and Validation of a Deep Learning-Based Model to Distinguish Glioblastoma from Solitary Brain Metastasis Using Conventional MR Images.
    Shin I; Kim H; Ahn SS; Sohn B; Bae S; Park JE; Kim HS; Lee SK
    AJNR Am J Neuroradiol; 2021 May; 42(5):838-844. PubMed ID: 33737268
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine.
    Perkuhn M; Stavrinou P; Thiele F; Shakirin G; Mohan M; Garmpis D; Kabbasch C; Borggrefe J
    Invest Radiol; 2018 Nov; 53(11):647-654. PubMed ID: 29863600
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model.
    Xia W; Hu B; Li H; Shi W; Tang Y; Yu Y; Geng C; Wu Q; Yang L; Yu Z; Geng D; Li Y
    J Magn Reson Imaging; 2021 Sep; 54(3):880-887. PubMed ID: 33694250
    [TBL] [Abstract][Full Text] [Related]  

  • 6. [Fully Automatic Glioma Segmentation Algorithm of Magnetic Resonance Imaging Based on 3D-UNet With More Global Contextual Feature Extraction: An Improvement on Insufficient Extraction of Global Features].
    Tian H; Wang Y; Ji Y; Rahman MM
    Sichuan Da Xue Xue Bao Yi Xue Ban; 2024 Mar; 55(2):447-454. PubMed ID: 38645864
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm.
    Yan Q; Li F; Cui Y; Wang Y; Wang X; Jia W; Liu X; Li Y; Chang H; Shi F; Xia Y; Zhou Q; Zeng Q
    J Digit Imaging; 2023 Aug; 36(4):1480-1488. PubMed ID: 37156977
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI.
    Grøvik E; Yi D; Iv M; Tong E; Rubin D; Zaharchuk G
    J Magn Reson Imaging; 2020 Jan; 51(1):175-182. PubMed ID: 31050074
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis.
    Artzi M; Bressler I; Ben Bashat D
    J Magn Reson Imaging; 2019 Aug; 50(2):519-528. PubMed ID: 30635952
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning With an Attention Mechanism for Differentiating the Origin of Brain Metastasis Using MR images.
    Jiao T; Li F; Cui Y; Wang X; Li B; Shi F; Xia Y; Zhou Q; Zeng Q
    J Magn Reson Imaging; 2023 Nov; 58(5):1624-1635. PubMed ID: 36965182
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Three-dimensional Deep Convolutional Neural Networks for Automated Myocardial Scar Quantification in Hypertrophic Cardiomyopathy: A Multicenter Multivendor Study.
    Fahmy AS; Neisius U; Chan RH; Rowin EJ; Manning WJ; Maron MS; Nezafat R
    Radiology; 2020 Jan; 294(1):52-60. PubMed ID: 31714190
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Robust performance of deep learning for distinguishing glioblastoma from single brain metastasis using radiomic features: model development and validation.
    Bae S; An C; Ahn SS; Kim H; Han K; Kim SW; Park JE; Kim HS; Lee SK
    Sci Rep; 2020 Jul; 10(1):12110. PubMed ID: 32694637
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.
    Kleesiek J; Urban G; Hubert A; Schwarz D; Maier-Hein K; Bendszus M; Biller A
    Neuroimage; 2016 Apr; 129():460-469. PubMed ID: 26808333
    [TBL] [Abstract][Full Text] [Related]  

  • 15. IDH1 mutation prediction using MR-based radiomics in glioblastoma: comparison between manual and fully automated deep learning-based approach of tumor segmentation.
    Choi Y; Nam Y; Lee YS; Kim J; Ahn KJ; Jang J; Shin NY; Kim BS; Jeon SS
    Eur J Radiol; 2020 Jul; 128():109031. PubMed ID: 32417712
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Reliability of Semi-Automated Segmentations in Glioblastoma.
    Huber T; Alber G; Bette S; Boeckh-Behrens T; Gempt J; Ringel F; Alberts E; Zimmer C; Bauer JS
    Clin Neuroradiol; 2017 Jun; 27(2):153-161. PubMed ID: 26490369
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma.
    Patel M; Zhan J; Natarajan K; Flintham R; Davies N; Sanghera P; Grist J; Duddalwar V; Peet A; Sawlani V
    Clin Radiol; 2021 Aug; 76(8):628.e17-628.e27. PubMed ID: 33941364
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI.
    Dikici E; Ryu JL; Demirer M; Bigelow M; White RD; Slone W; Erdal BS; Prevedello LM
    IEEE J Biomed Health Inform; 2020 Oct; 24(10):2883-2893. PubMed ID: 32203040
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Deep Convolutional Neural Network With Performance Comparable to Radiologists for Differentiating Between Spinal Schwannoma and Meningioma.
    Maki S; Furuya T; Horikoshi T; Yokota H; Mori Y; Ota J; Kawasaki Y; Miyamoto T; Norimoto M; Okimatsu S; Shiga Y; Inage K; Orita S; Takahashi H; Suyari H; Uno T; Ohtori S
    Spine (Phila Pa 1976); 2020 May; 45(10):694-700. PubMed ID: 31809468
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning based differentiation of glioblastoma from brain metastasis using MRI derived radiomics.
    Priya S; Liu Y; Ward C; Le NH; Soni N; Pillenahalli Maheshwarappa R; Monga V; Zhang H; Sonka M; Bathla G
    Sci Rep; 2021 May; 11(1):10478. PubMed ID: 34006893
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.