BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

182 related articles for article (PubMed ID: 35624544)

  • 1. Automated Detection of Brain Metastases on T1-Weighted MRI Using a Convolutional Neural Network: Impact of Volume Aware Loss and Sampling Strategy.
    Chartrand G; Emiliani RD; Pawlowski SA; Markel DA; Bahig H; Cengarle-Samak A; Rajakesari S; Lavoie J; Ducharme S; Roberge D
    J Magn Reson Imaging; 2022 Dec; 56(6):1885-1898. PubMed ID: 35624544
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Gradual Self-Training via Confidence and Volume Based Domain Adaptation for Multi Dataset Deep Learning-Based Brain Metastases Detection Using Nonlocal Networks on MRI Images.
    Liew A; Lee CC; Subramaniam V; Lan BL; Tan M
    J Magn Reson Imaging; 2023 Jun; 57(6):1728-1740. PubMed ID: 36208095
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Fully Automated MR Detection and Segmentation of Brain Metastases in Non-small Cell Lung Cancer Using Deep Learning.
    Jünger ST; Hoyer UCI; Schaufler D; Laukamp KR; Goertz L; Thiele F; Grunz JP; Schlamann M; Perkuhn M; Kabbasch C; Persigehl T; Grau S; Borggrefe J; Scheffler M; Shahzad R; Pennig L
    J Magn Reson Imaging; 2021 Nov; 54(5):1608-1622. PubMed ID: 34032344
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data.
    Bousabarah K; Ruge M; Brand JS; Hoevels M; Rueß D; Borggrefe J; Große Hokamp N; Visser-Vandewalle V; Maintz D; Treuer H; Kocher M
    Radiat Oncol; 2020 Apr; 15(1):87. PubMed ID: 32312276
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks.
    Said D; Carbonell G; Stocker D; Hectors S; Vietti-Violi N; Bane O; Chin X; Schwartz M; Tabrizian P; Lewis S; Greenspan H; Jégou S; Schiratti JB; Jehanno P; Taouli B
    Eur Radiol; 2023 Sep; 33(9):6020-6032. PubMed ID: 37071167
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Construction and evaluation of a gated high-resolution neural network for automatic brain metastasis detection and segmentation.
    Qu J; Zhang W; Shu X; Wang Y; Wang L; Xu M; Yao L; Hu N; Tang B; Zhang L; Lui S
    Eur Radiol; 2023 Oct; 33(10):6648-6658. PubMed ID: 37186214
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.
    Kang H; Witanto JN; Pratama K; Lee D; Choi KS; Choi SH; Kim KM; Kim MS; Kim JW; Kim YH; Park SJ; Park CK
    J Magn Reson Imaging; 2023 Mar; 57(3):871-881. PubMed ID: 35775971
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep learning for brain metastasis detection and segmentation in longitudinal MRI data.
    Huang Y; Bert C; Sommer P; Frey B; Gaipl U; Distel LV; Weissmann T; Uder M; Schmidt MA; Dörfler A; Maier A; Fietkau R; Putz F
    Med Phys; 2022 Sep; 49(9):5773-5786. PubMed ID: 35833351
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Automatic segmentation of brain metastases using T1 magnetic resonance and computed tomography images.
    Hsu DG; Ballangrud Å; Shamseddine A; Deasy JO; Veeraraghavan H; Cervino L; Beal K; Aristophanous M
    Phys Med Biol; 2021 Aug; 66(17):. PubMed ID: 34315148
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Augmented networks for faster brain metastases detection in T1-weighted contrast-enhanced 3D MRI.
    Dikici E; Nguyen XV; Bigelow M; Prevedello LM
    Comput Med Imaging Graph; 2022 Jun; 98():102059. PubMed ID: 35395606
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 3D Breast Cancer Segmentation in DCE-MRI Using Deep Learning With Weak Annotation.
    Park GE; Kim SH; Nam Y; Kang J; Park M; Kang BJ
    J Magn Reson Imaging; 2024 Jun; 59(6):2252-2262. PubMed ID: 37596823
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep Learning-Based Automatic Detection of Brain Metastases in Heterogenous Multi-Institutional Magnetic Resonance Imaging Sets: An Exploratory Analysis of NRG-CC001.
    Liang Y; Lee K; Bovi JA; Palmer JD; Brown PD; Gondi V; Tomé WA; Benzinger TLS; Mehta MP; Li XA
    Int J Radiat Oncol Biol Phys; 2022 Nov; 114(3):529-536. PubMed ID: 35787927
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic detection and segmentation of multiple brain metastases on magnetic resonance image using asymmetric UNet architecture.
    Cao Y; Vassantachart A; Ye JC; Yu C; Ruan D; Sheng K; Lao Y; Shen ZL; Balik S; Bian S; Zada G; Shiu A; Chang EL; Yang W
    Phys Med Biol; 2021 Jan; 66(1):015003. PubMed ID: 33186927
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MRI-based two-stage deep learning model for automatic detection and segmentation of brain metastases.
    Li R; Guo Y; Zhao Z; Chen M; Liu X; Gong G; Wang L
    Eur Radiol; 2023 May; 33(5):3521-3531. PubMed ID: 36695903
    [TBL] [Abstract][Full Text] [Related]  

  • 17. An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.
    Fashandi H; Kuling G; Lu Y; Wu H; Martel AL
    Med Phys; 2019 Mar; 46(3):1230-1244. PubMed ID: 30609062
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep-Learning-Based Neural Tissue Segmentation of MRI in Multiple Sclerosis: Effect of Training Set Size.
    Narayana PA; Coronado I; Sujit SJ; Wolinsky JS; Lublin FD; Gabr RE
    J Magn Reson Imaging; 2020 May; 51(5):1487-1496. PubMed ID: 31625650
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Segmentation of the Aorta and Pulmonary Arteries Based on 4D Flow MRI in the Pediatric Setting Using Fully Automated Multi-Site, Multi-Vendor, and Multi-Label Dense U-Net.
    Fujiwara T; Berhane H; Scott MB; Englund EK; Schäfer M; Fonseca B; Berthusen A; Robinson JD; Rigsby CK; Browne LP; Markl M; Barker AJ
    J Magn Reson Imaging; 2022 Jun; 55(6):1666-1680. PubMed ID: 34792835
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.
    Astley JR; Biancardi AM; Hughes PJC; Marshall H; Collier GJ; Chan HF; Saunders LC; Smith LJ; Brook ML; Thompson R; Rowland-Jones S; Skeoch S; Bianchi SM; Hatton MQ; Rahman NM; Ho LP; Brightling CE; Wain LV; Singapuri A; Evans RA; Moss AJ; McCann GP; Neubauer S; Raman B; ; Wild JM; Tahir BA
    J Magn Reson Imaging; 2023 Oct; 58(4):1030-1044. PubMed ID: 36799341
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.