BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

424 related articles for article (PubMed ID: 28681390)

  • 1. A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.
    Antropova N; Huynh BQ; Giger ML
    Med Phys; 2017 Oct; 44(10):5162-5171. PubMed ID: 28681390
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.
    Kooi T; van Ginneken B; Karssemeijer N; den Heeten A
    Med Phys; 2017 Mar; 44(3):1017-1027. PubMed ID: 28094850
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A computer-aided diagnosis system for breast DCE-MRI at high spatiotemporal resolution.
    Dalmış MU; Gubern-Mérida A; Vreemann S; Karssemeijer N; Mann R; Platel B
    Med Phys; 2016 Jan; 43(1):84. PubMed ID: 26745902
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI.
    Hu Q; Whitney HM; Giger ML
    Sci Rep; 2020 Jun; 10(1):10536. PubMed ID: 32601367
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.
    Hu X; Gong J; Zhou W; Li H; Wang S; Wei M; Peng W; Gu Y
    Phys Med Biol; 2021 Mar; 66(6):065015. PubMed ID: 33596552
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Potential of computer-aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions.
    Bhooshan N; Giger M; Medved M; Li H; Wood A; Yuan Y; Lan L; Marquez A; Karczmar G; Newstead G
    J Magn Reson Imaging; 2014 Jan; 39(1):59-67. PubMed ID: 24023011
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep Convolutional Neural Networks for breast cancer screening.
    Chougrad H; Zouaki H; Alheyane O
    Comput Methods Programs Biomed; 2018 Apr; 157():19-30. PubMed ID: 29477427
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep feature-based automatic classification of mammograms.
    Arora R; Rai PK; Raman B
    Med Biol Eng Comput; 2020 Jun; 58(6):1199-1211. PubMed ID: 32200453
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparison of Breast MRI Tumor Classification Using Human-Engineered Radiomics, Transfer Learning From Deep Convolutional Neural Networks, and Fusion Methods.
    Whitney HM; Li H; Ji Y; Liu P; Giger ML
    Proc IEEE Inst Electr Electron Eng; 2020 Jan; 108(1):163-177. PubMed ID: 34045769
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Computer-aided diagnosis of masses in breast computed tomography imaging: deep learning model with combined handcrafted and convolutional radiomic features.
    Caballo M; Hernandez AM; Lyu SH; Teuwen J; Mann RM; van Ginneken B; Boone JM; Sechopoulos I
    J Med Imaging (Bellingham); 2021 Mar; 8(2):024501. PubMed ID: 33796604
    [No Abstract]   [Full Text] [Related]  

  • 11. A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.
    Wang H; Zhao T; Li LC; Pan H; Liu W; Gao H; Han F; Wang Y; Qi Y; Liang Z
    J Xray Sci Technol; 2018; 26(2):171-187. PubMed ID: 29036877
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.
    Sun W; Zheng B; Qian W
    Comput Biol Med; 2017 Oct; 89():530-539. PubMed ID: 28473055
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.
    Milenković J; Hertl K; Košir A; Zibert J; Tasič JF
    Artif Intell Med; 2013 Jun; 58(2):101-14. PubMed ID: 23548472
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Evaluation of clinical breast MR imaging performed with prototype computer-aided diagnosis breast MR imaging workstation: reader study.
    Shimauchi A; Giger ML; Bhooshan N; Lan L; Pesce LL; Lee JK; Abe H; Newstead GM
    Radiology; 2011 Mar; 258(3):696-704. PubMed ID: 21212365
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Classification of benign and malignant masses based on Zernike moments.
    Tahmasbi A; Saki F; Shokouhi SB
    Comput Biol Med; 2011 Aug; 41(8):726-35. PubMed ID: 21722886
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.
    Bandeira Diniz JO; Bandeira Diniz PH; Azevedo Valente TL; Corrêa Silva A; de Paiva AC; Gattass M
    Comput Methods Programs Biomed; 2018 Mar; 156():191-207. PubMed ID: 29428071
    [TBL] [Abstract][Full Text] [Related]  

  • 17. SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis.
    Gao F; Wu T; Li J; Zheng B; Ruan L; Shang D; Patel B
    Comput Med Imaging Graph; 2018 Dec; 70():53-62. PubMed ID: 30292910
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A graph-based lesion characterization and deep embedding approach for improved computer-aided diagnosis of nonmass breast MRI lesions.
    Gallego-Ortiz C; Martel AL
    Med Image Anal; 2019 Jan; 51():116-124. PubMed ID: 30412826
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT.
    Lee J; Nishikawa RM; Reiser I; Boone JM
    Med Phys; 2017 May; 44(5):1846-1856. PubMed ID: 28295405
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Assessment of a Four-View Mammographic Image Feature Based Fusion Model to Predict Near-Term Breast Cancer Risk.
    Tan M; Pu J; Cheng S; Liu H; Zheng B
    Ann Biomed Eng; 2015 Oct; 43(10):2416-28. PubMed ID: 25851469
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 22.