BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

199 related articles for article (PubMed ID: 36287799)

  • 1. Improving Performance of Breast Lesion Classification Using a ResNet50 Model Optimized with a Novel Attention Mechanism.
    Islam W; Jones M; Faiz R; Sadeghipour N; Qiu Y; Zheng B
    Tomography; 2022 Sep; 8(5):2411-2425. PubMed ID: 36287799
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.
    Qiu Y; Yan S; Gundreddy RR; Wang Y; Cheng S; Liu H; Zheng B
    J Xray Sci Technol; 2017; 25(5):751-763. PubMed ID: 28436410
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.
    Samala RK; Chan HP; Hadjiiski L; Helvie MA; Wei J; Cha K
    Med Phys; 2016 Dec; 43(12):6654. PubMed ID: 27908154
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multi-scale attention-based convolutional neural network for classification of breast masses in mammograms.
    Niu J; Li H; Zhang C; Li D
    Med Phys; 2021 Jul; 48(7):3878-3892. PubMed ID: 33982807
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Mammogram classification based on a novel convolutional neural network with efficient channel attention.
    Lou Q; Li Y; Qian Y; Lu F; Ma J
    Comput Biol Med; 2022 Nov; 150():106082. PubMed ID: 36195044
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Assessment of performance and reproducibility of applying a content-based image retrieval scheme for classification of breast lesions.
    Gundreddy RR; Tan M; Qiu Y; Cheng S; Liu H; Zheng B
    Med Phys; 2015 Jul; 42(7):4241-9. PubMed ID: 26133622
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. 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]  

  • 9. 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]  

  • 10. Attention-based deep learning for breast lesions classification on contrast enhanced spectral mammography: a multicentre study.
    Mao N; Zhang H; Dai Y; Li Q; Lin F; Gao J; Zheng T; Zhao F; Xie H; Xu C; Ma H
    Br J Cancer; 2023 Mar; 128(5):793-804. PubMed ID: 36522478
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning-based Automatic Diagnosis of Breast Cancer on MRI Using Mask R-CNN for Detection Followed by ResNet50 for Classification.
    Zhang Y; Liu YL; Nie K; Zhou J; Chen Z; Chen JH; Wang X; Kim B; Parajuli R; Mehta RS; Wang M; Su MY
    Acad Radiol; 2023 Sep; 30 Suppl 2(Suppl 2):S161-S171. PubMed ID: 36631349
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods.
    Danala G; Maryada SK; Islam W; Faiz R; Jones M; Qiu Y; Zheng B
    Bioengineering (Basel); 2022 Jun; 9(6):. PubMed ID: 35735499
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 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. Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.
    Al-Masni MA; Al-Antari MA; Park JM; Gi G; Kim TY; Rivera P; Valarezo E; Choi MT; Han SM; Kim TS
    Comput Methods Programs Biomed; 2018 Apr; 157():85-94. PubMed ID: 29477437
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.
    Al-Antari MA; Al-Masni MA; Kim TS
    Adv Exp Med Biol; 2020; 1213():59-72. PubMed ID: 32030663
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms.
    Al-Antari MA; Han SM; Kim TS
    Comput Methods Programs Biomed; 2020 Nov; 196():105584. PubMed ID: 32554139
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An experimental study on breast lesion detection and classification from ultrasound images using deep learning architectures.
    Cao Z; Duan L; Yang G; Yue T; Chen Q
    BMC Med Imaging; 2019 Jul; 19(1):51. PubMed ID: 31262255
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms.
    Samala RK; Chan HP; Hadjiiski LM; Helvie MA; Cha KH; Richter CD
    Phys Med Biol; 2017 Nov; 62(23):8894-8908. PubMed ID: 29035873
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.