BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

157 related articles for article (PubMed ID: 33459385)

  • 1. 3D Inception U-net with Asymmetric Loss for Cancer Detection in Automated Breast Ultrasound.
    Wang Y; Qin C; Lin C; Lin D; Xu M; Luo X; Wang T; Li A; Ni D
    Med Phys; 2020 Nov; 47(11):5582-5591. PubMed ID: 33459385
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.
    Wang Y; Wang N; Xu M; Yu J; Qin C; Luo X; Yang X; Wang T; Li A; Ni D
    IEEE Trans Med Imaging; 2020 Apr; 39(4):866-876. PubMed ID: 31442972
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computer-aided tumor detection in automated breast ultrasound using a 3-D convolutional neural network.
    Moon WK; Huang YS; Hsu CH; Chang Chien TY; Chang JM; Lee SH; Huang CS; Chang RF
    Comput Methods Programs Biomed; 2020 Jul; 190():105360. PubMed ID: 32007838
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 3D tumor detection in automated breast ultrasound using deep convolutional neural network.
    Li Y; Wu W; Chen H; Cheng L; Wang S
    Med Phys; 2020 Nov; 47(11):5669-5680. PubMed ID: 32970838
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Three-dimensional automated breast ultrasound: Technical aspects and first results.
    Vourtsis A
    Diagn Interv Imaging; 2019 Oct; 100(10):579-592. PubMed ID: 30962169
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A 2-Phase Merge Filter Approach to Computer-Aided Detection of Breast Tumors on 3-Dimensional Ultrasound Imaging.
    Chiu LY; Kuo WH; Chen CN; Chang KJ; Chen A
    J Ultrasound Med; 2020 Dec; 39(12):2439-2455. PubMed ID: 32567133
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts.
    van Zelst JCM; Tan T; Clauser P; Domingo A; Dorrius MD; Drieling D; Golatta M; Gras F; de Jong M; Pijnappel R; Rutten MJCM; Karssemeijer N; Mann RM
    Eur Radiol; 2018 Jul; 28(7):2996-3006. PubMed ID: 29417251
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation.
    Chiang TC; Huang YS; Chen RT; Huang CS; Chang RF
    IEEE Trans Med Imaging; 2019 Jan; 38(1):240-249. PubMed ID: 30059297
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Auto-DenseUNet: Searchable neural network architecture for mass segmentation in 3D automated breast ultrasound.
    Cao X; Chen H; Li Y; Peng Y; Zhou Y; Cheng L; Liu T; Shen D
    Med Image Anal; 2022 Nov; 82():102589. PubMed ID: 36095905
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Breast Cancer Classification in Automated Breast Ultrasound Using Multiview Convolutional Neural Network with Transfer Learning.
    Wang Y; Choi EJ; Choi Y; Zhang H; Jin GY; Ko SB
    Ultrasound Med Biol; 2020 May; 46(5):1119-1132. PubMed ID: 32059918
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Multi-dimensional tumor detection in automated whole breast ultrasound using topographic watershed.
    Lo CM; Chen RT; Chang YC; Yang YW; Hung MJ; Huang CS; Chang RF
    IEEE Trans Med Imaging; 2014 Jul; 33(7):1503-11. PubMed ID: 24718570
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Breast tumor segmentation in 3D automatic breast ultrasound using Mask scoring R-CNN.
    Lei Y; He X; Yao J; Wang T; Wang L; Li W; Curran WJ; Liu T; Xu D; Yang X
    Med Phys; 2021 Jan; 48(1):204-214. PubMed ID: 33128230
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Adding 3D automated breast ultrasound to mammography screening in women with heterogeneously and extremely dense breasts: Report from a hospital-based, high-volume, single-center breast cancer screening program.
    Wilczek B; Wilczek HE; Rasouliyan L; Leifland K
    Eur J Radiol; 2016 Sep; 85(9):1554-63. PubMed ID: 27501888
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Computer-aided detection of breast cancers using Haar-like features in automated 3D breast ultrasound.
    Tan T; Mordang JJ; van Zelst J; Grivegnée A; Gubern-Mérida A; Melendez J; Mann RM; Zhang W; Platel B; Karssemeijer N
    Med Phys; 2015 Apr; 42(4):1498-504. PubMed ID: 25832040
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts.
    Drukker K; Sennett CA; Giger ML
    Med Phys; 2014 Jan; 41(1):012901. PubMed ID: 24387528
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Lesion Segmentation in Automated 3D Breast Ultrasound: Volumetric Analysis.
    Agarwal R; Diaz O; Lladó X; Gubern-Mérida A; Vilanova JC; Martí R
    Ultrason Imaging; 2018 Mar; 40(2):97-112. PubMed ID: 29182056
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Interpretation of automated breast ultrasound (ABUS) with and without knowledge of mammography: a reader performance study.
    Skaane P; Gullien R; Eben EB; Sandhaug M; Schulz-Wendtland R; Stoeblen F
    Acta Radiol; 2015 Apr; 56(4):404-12. PubMed ID: 24682405
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Fully automatic classification of automated breast ultrasound (ABUS) imaging according to BI-RADS using a deep convolutional neural network.
    Hejduk P; Marcon M; Unkelbach J; Ciritsis A; Rossi C; Borkowski K; Boss A
    Eur Radiol; 2022 Jul; 32(7):4868-4878. PubMed ID: 35147776
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Dilated densely connected U-Net with uncertainty focus loss for 3D ABUS mass segmentation.
    Cao X; Chen H; Li Y; Peng Y; Wang S; Cheng L
    Comput Methods Programs Biomed; 2021 Sep; 209():106313. PubMed ID: 34364182
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Tumor segmentation in automated whole breast ultrasound using bidirectional LSTM neural network and attention mechanism.
    Pan P; Chen H; Li Y; Cai N; Cheng L; Wang S
    Ultrasonics; 2021 Feb; 110():106271. PubMed ID: 33166786
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.