BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

262 related articles for article (PubMed ID: 31918376)

  • 1. Segmentation of bones in medical dual-energy computed tomography volumes using the 3D U-Net.
    González Sánchez JC; Magnusson M; Sandborg M; Carlsson Tedgren Å; Malusek A
    Phys Med; 2020 Jan; 69():241-247. PubMed ID: 31918376
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Complete abdomen and pelvis segmentation using U-net variant architecture.
    Weston AD; Korfiatis P; Philbrick KA; Conte GM; Kostandy P; Sakinis T; Zeinoddini A; Boonrod A; Moynagh M; Takahashi N; Erickson BJ
    Med Phys; 2020 Nov; 47(11):5609-5618. PubMed ID: 32740931
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep learning from dual-energy information for whole-heart segmentation in dual-energy and single-energy non-contrast-enhanced cardiac CT.
    Bruns S; Wolterink JM; Takx RAP; van Hamersvelt RW; Suchá D; Viergever MA; Leiner T; Išgum I
    Med Phys; 2020 Oct; 47(10):5048-5060. PubMed ID: 32786071
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DENSE-INception U-net for medical image segmentation.
    Zhang Z; Wu C; Coleman S; Kerr D
    Comput Methods Programs Biomed; 2020 Aug; 192():105395. PubMed ID: 32163817
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep convolutional neural network for segmentation of knee joint anatomy.
    Zhou Z; Zhao G; Kijowski R; Liu F
    Magn Reson Med; 2018 Dec; 80(6):2759-2770. PubMed ID: 29774599
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
    Zhu W; Huang Y; Zeng L; Chen X; Liu Y; Qian Z; Du N; Fan W; Xie X
    Med Phys; 2019 Feb; 46(2):576-589. PubMed ID: 30480818
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
    Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH
    Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Liver tumor segmentation based on 3D convolutional neural network with dual scale.
    Meng L; Tian Y; Bu S
    J Appl Clin Med Phys; 2020 Jan; 21(1):144-157. PubMed ID: 31793212
    [TBL] [Abstract][Full Text] [Related]  

  • 11. U-Net based deep learning bladder segmentation in CT urography.
    Ma X; Hadjiiski LM; Wei J; Chan HP; Cha KH; Cohan RH; Caoili EM; Samala R; Zhou C; Lu Y
    Med Phys; 2019 Apr; 46(4):1752-1765. PubMed ID: 30734932
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Image domain dual material decomposition for dual-energy CT using butterfly network.
    Zhang W; Zhang H; Wang L; Wang X; Hu X; Cai A; Li L; Niu T; Yan B
    Med Phys; 2019 May; 46(5):2037-2051. PubMed ID: 30883808
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks.
    Chen S; Zhong X; Hu S; Dorn S; Kachelrieß M; Lell M; Maier A
    Med Phys; 2020 Feb; 47(2):552-562. PubMed ID: 31816095
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Improving segmentation and classification of renal tumors in small sample 3D CT images using transfer learning with convolutional neural networks.
    Zhu XL; Shen HB; Sun H; Duan LX; Xu YY
    Int J Comput Assist Radiol Surg; 2022 Jul; 17(7):1303-1311. PubMed ID: 35290645
    [TBL] [Abstract][Full Text] [Related]  

  • 15. OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions.
    Heinrich MP; Oktay O; Bouteldja N
    Med Image Anal; 2019 May; 54():1-9. PubMed ID: 30807894
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Design of lung nodules segmentation and recognition algorithm based on deep learning.
    Yu H; Li J; Zhang L; Cao Y; Yu X; Sun J
    BMC Bioinformatics; 2021 Nov; 22(Suppl 5):314. PubMed ID: 34749636
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Fully automatic estimation of pelvic sagittal inclination from anterior-posterior radiography image using deep learning framework.
    Jodeiri A; Zoroofi RA; Hiasa Y; Takao M; Sugano N; Sato Y; Otake Y
    Comput Methods Programs Biomed; 2020 Feb; 184():105282. PubMed ID: 31896056
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation.
    Lee SB; Hong Y; Cho YJ; Jeong D; Lee J; Yoon SH; Lee S; Choi YH; Cheon JE
    Korean J Radiol; 2023 Apr; 24(4):294-304. PubMed ID: 36907592
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automated Segmentation of Colorectal Tumor in 3D MRI Using 3D Multiscale Densely Connected Convolutional Neural Network.
    Soomro MH; Coppotelli M; Conforto S; Schmid M; Giunta G; Del Secco L; Neri E; Caruso D; Rengo M; Laghi A
    J Healthc Eng; 2019; 2019():1075434. PubMed ID: 30838121
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.
    Ibragimov B; Xing L
    Med Phys; 2017 Feb; 44(2):547-557. PubMed ID: 28205307
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.