BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

110 related articles for article (PubMed ID: 35104686)

  • 1. A multi-task two-path deep learning system for predicting the invasiveness of craniopharyngioma.
    Zhu L; Zhang L; Hu W; Chen H; Li H; Wei S; Chen X; Ma X
    Comput Methods Programs Biomed; 2022 Apr; 216():106651. PubMed ID: 35104686
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automated segmentation of craniopharyngioma on MR images using U-Net-based deep convolutional neural network.
    Chen C; Zhang T; Teng Y; Yu Y; Shu X; Zhang L; Zhao F; Xu J
    Eur Radiol; 2023 Apr; 33(4):2665-2675. PubMed ID: 36396792
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep morphology aided diagnosis network for segmentation of carotid artery vessel wall and diagnosis of carotid atherosclerosis on black-blood vessel wall MRI.
    Wu J; Xin J; Yang X; Sun J; Xu D; Zheng N; Yuan C
    Med Phys; 2019 Dec; 46(12):5544-5561. PubMed ID: 31356693
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset.
    Panda A; Korfiatis P; Suman G; Garg SK; Polley EC; Singh DP; Chari ST; Goenka AH
    Med Phys; 2021 May; 48(5):2468-2481. PubMed ID: 33595105
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Craniopharyngioma adherence: a comprehensive topographical categorization and outcome-related risk stratification model based on the methodical examination of 500 tumors.
    Prieto R; Pascual JM; Rosdolsky M; Castro-Dufourny I; Carrasco R; Strauss S; Barrios L
    Neurosurg Focus; 2016 Dec; 41(6):E13. PubMed ID: 27903121
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.
    Kim M; Kim HS; Kim HJ; Park JE; Park SY; Kim YH; Kim SJ; Lee J; Lebel MR
    Radiology; 2021 Jan; 298(1):114-122. PubMed ID: 33141001
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images.
    Prince EW; Whelan R; Mirsky DM; Stence N; Staulcup S; Klimo P; Anderson RCE; Niazi TN; Grant G; Souweidane M; Johnston JM; Jackson EM; Limbrick DD; Smith A; Drapeau A; Chern JJ; Kilburn L; Ginn K; Naftel R; Dudley R; Tyler-Kabara E; Jallo G; Handler MH; Jones K; Donson AM; Foreman NK; Hankinson TC
    Sci Rep; 2020 Oct; 10(1):16885. PubMed ID: 33037266
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Feature-shared adaptive-boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images.
    Wang J; Chen X; Lu H; Zhang L; Pan J; Bao Y; Su J; Qian D
    Med Phys; 2020 Apr; 47(4):1738-1749. PubMed ID: 32020649
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Deep Learning Framework for Segmenting Brain Tumors Using MRI and Synthetically Generated CT Images.
    Islam KT; Wijewickrema S; O'Leary S
    Sensors (Basel); 2022 Jan; 22(2):. PubMed ID: 35062484
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images.
    El Adoui M; Drisis S; Benjelloun M
    Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1491-1500. PubMed ID: 32556920
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Development and Evaluation of Deep Learning-based Automated Segmentation of Pituitary Adenoma in Clinical Task.
    Wang H; Zhang W; Li S; Fan Y; Feng M; Wang R
    J Clin Endocrinol Metab; 2021 Aug; 106(9):2535-2546. PubMed ID: 34060609
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [Magnetic resonance imaging characteristics and differential diagnosis of common sellar cystic lesions].
    Liu H; Lu X; Hang W; Liu G
    Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi; 2019 Nov; 54(11):819-825. PubMed ID: 31795542
    [No Abstract]   [Full Text] [Related]  

  • 13. Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach.
    Chen X; Tong Y; Shi Z; Chen H; Yang Z; Wang Y; Chen L; Yu J
    BMC Neurol; 2019 Jan; 19(1):6. PubMed ID: 30616515
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Endoscopic endonasal approach for craniopharyngioma: the importance of the relationship between pituitary stalk and tumor.
    Dho YS; Kim YH; Se YB; Han DH; Kim JH; Park CK; Wang KC; Kim DG
    J Neurosurg; 2018 Sep; 129(3):611-619. PubMed ID: 28960155
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.
    Bien N; Rajpurkar P; Ball RL; Irvin J; Park A; Jones E; Bereket M; Patel BN; Yeom KW; Shpanskaya K; Halabi S; Zucker E; Fanton G; Amanatullah DF; Beaulieu CF; Riley GM; Stewart RJ; Blankenberg FG; Larson DB; Jones RH; Langlotz CP; Ng AY; Lungren MP
    PLoS Med; 2018 Nov; 15(11):e1002699. PubMed ID: 30481176
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.
    Zhang L; Mohamed AA; Chai R; Guo Y; Zheng B; Wu S
    J Magn Reson Imaging; 2020 Feb; 51(2):635-643. PubMed ID: 31301201
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparison of Prostate MRI Lesion Segmentation Agreement Between Multiple Radiologists and a Fully Automatic Deep Learning System.
    Schelb P; Tavakoli AA; Tubtawee T; Hielscher T; Radtke JP; Görtz M; Schütz V; Kuder TA; Schimmöller L; Stenzinger A; Hohenfellner M; Schlemmer HP; Bonekamp D
    Rofo; 2021 May; 193(5):559-573. PubMed ID: 33212541
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
    Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
    Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.
    Chen Y; Xing L; Yu L; Bagshaw HP; Buyyounouski MK; Han B
    Med Phys; 2020 Dec; 47(12):6421-6429. PubMed ID: 33012016
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 6.