BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

159 related articles for article (PubMed ID: 34049119)

  • 1. Pattern classification for breast lesion on FFDM by integration of radiomics and deep features.
    Zhang X; Liang C; Zeng D; Jiang X; Zhong R; Lan Y; Ma J; Bai L
    Comput Med Imaging Graph; 2021 Jun; 90():101922. PubMed ID: 34049119
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A computer-aided diagnosis scheme of breast lesion classification using GLGLM and shape features: Combined-view and multi-classifiers.
    Liang C; Bian Z; Lv W; Chen S; Zeng D; Ma J
    Phys Med; 2018 Nov; 55():61-72. PubMed ID: 30471821
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.
    Mendel K; Li H; Sheth D; Giger M
    Acad Radiol; 2019 Jun; 26(6):735-743. PubMed ID: 30076083
    [TBL] [Abstract][Full Text] [Related]  

  • 4. [Establishment of a deep feature-based classification model for distinguishing benign and malignant breast tumors on full-filed digital mammography].
    Liang C; Li M; Bian Z; Lv W; Zeng D; Ma J
    Nan Fang Yi Ke Da Xue Xue Bao; 2019 Jan; 39(1):88-92. PubMed ID: 30692072
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A multi-stage fusion framework to classify breast lesions using deep learning and radiomics features computed from four-view mammograms.
    Jones MA; Sadeghipour N; Chen X; Islam W; Zheng B
    Med Phys; 2023 Dec; 50(12):7670-7683. PubMed ID: 37083190
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Combining Deep Learning and Handcrafted Radiomics for Classification of Suspicious Lesions on Contrast-enhanced Mammograms.
    Beuque MPL; Lobbes MBI; van Wijk Y; Widaatalla Y; Primakov S; Majer M; Balleyguier C; Woodruff HC; Lambin P
    Radiology; 2023 Jun; 307(5):e221843. PubMed ID: 37338353
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification.
    Li X; Qin G; He Q; Sun L; Zeng H; He Z; Chen W; Zhen X; Zhou L
    Eur Radiol; 2020 Feb; 30(2):778-788. PubMed ID: 31691121
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparison of radiologist performance with photon-counting full-field digital mammography to conventional full-field digital mammography.
    Cole EB; Toledano AY; Lundqvist M; Pisano ED
    Acad Radiol; 2012 Aug; 19(8):916-22. PubMed ID: 22537503
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improving the malignancy prediction of breast cancer based on the integration of radiomics features from dual-view mammography and clinical parameters.
    Zhou C; Xie H; Zhu F; Yan W; Yu R; Wang Y
    Clin Exp Med; 2023 Oct; 23(6):2357-2368. PubMed ID: 36413273
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Detection and characterization of breast lesions in a selective diagnostic population: diagnostic accuracy study for comparison between one-view digital breast tomosynthesis and two-view full-field digital mammography.
    Chae EY; Kim HH; Cha JH; Shin HJ; Choi WJ
    Br J Radiol; 2016 Jun; 89(1062):20150743. PubMed ID: 27072391
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Digital Mammography in Breast Cancer: Additive Value of Radiomics of Breast Parenchyma.
    Li H; Mendel KR; Lan L; Sheth D; Giger ML
    Radiology; 2019 Apr; 291(1):15-20. PubMed ID: 30747591
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Combination of one-view digital breast tomosynthesis with one-view digital mammography versus standard two-view digital mammography: per lesion analysis.
    Gennaro G; Hendrick RE; Toledano A; Paquelet JR; Bezzon E; Chersevani R; di Maggio C; La Grassa M; Pescarini L; Polico I; Proietti A; Baldan E; Pomerri F; Muzzio PC
    Eur Radiol; 2013 Aug; 23(8):2087-94. PubMed ID: 23620367
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of two-dimensional synthesized mammograms versus original digital mammograms: a quantitative assessment.
    Tan M; Al-Shabi M; Chan WY; Thomas L; Rahmat K; Ng KH
    Med Biol Eng Comput; 2021 Feb; 59(2):355-367. PubMed ID: 33447988
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features.
    Jones MA; Faiz R; Qiu Y; Zheng B
    Phys Med Biol; 2022 Feb; 67(5):. PubMed ID: 35130517
    [No Abstract]   [Full Text] [Related]  

  • 15. Evaluating the HER-2 status of breast cancer using mammography radiomics features.
    Zhou J; Tan H; Bai Y; Li J; Lu Q; Chen R; Zhang M; Feng Q; Wang M
    Eur J Radiol; 2019 Dec; 121():108718. PubMed ID: 31711023
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A radiomics method to classify microcalcification clusters in digital breast tomosynthesis.
    Peng Y; Wu S; Yuan G; Wu Z; Du Q; Sun H; Yang X; Chen Q; Zheng J
    Med Phys; 2020 Aug; 47(8):3435-3446. PubMed ID: 32358973
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Radiomics Based on Digital Mammography Helps to Identify Mammographic Masses Suspicious for Cancer.
    Wang G; Shi D; Guo Q; Zhang H; Wang S; Ren K
    Front Oncol; 2022; 12():843436. PubMed ID: 35433437
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Multi-region radiomics for artificially intelligent diagnosis of breast cancer using multimodal ultrasound.
    Xu Z; Wang Y; Chen M; Zhang Q
    Comput Biol Med; 2022 Oct; 149():105920. PubMed ID: 35986969
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Diagnosis of architectural distortion on digital breast tomosynthesis using radiomics and deep learning.
    Chen X; Zhang Y; Zhou J; Wang X; Liu X; Nie K; Lin X; He W; Su MY; Cao G; Wang M
    Front Oncol; 2022; 12():991892. PubMed ID: 36582788
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Diagnostic performance of perilesional radiomics analysis of contrast-enhanced mammography for the differentiation of benign and malignant breast lesions.
    Wang S; Sun Y; Li R; Mao N; Li Q; Jiang T; Chen Q; Duan S; Xie H; Gu Y
    Eur Radiol; 2022 Jan; 32(1):639-649. PubMed ID: 34189600
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.