BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

164 related articles for article (PubMed ID: 28845077)

  • 1. 3D Convolutional Neural Network for Automatic Detection of Lung Nodules in Chest CT.
    Hamidian S; Sahiner B; Petrick N; Pezeshk A
    Proc SPIE Int Soc Opt Eng; 2017; 10134():. PubMed ID: 28845077
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans.
    Farhangi MM; Petrick N; Sahiner B; Frigui H; Amini AA; Pezeshk A
    Med Phys; 2020 Jun; 47(5):2150-2160. PubMed ID: 32030769
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Fast and fully-automated detection and segmentation of pulmonary nodules in thoracic CT scans using deep convolutional neural networks.
    Huang X; Sun W; Tseng TB; Li C; Qian W
    Comput Med Imaging Graph; 2019 Jun; 74():25-36. PubMed ID: 30954678
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT.
    Pezeshk A; Hamidian S; Petrick N; Sahiner B
    IEEE J Biomed Health Inform; 2019 Sep; 23(5):2080-2090. PubMed ID: 30418929
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.
    Dong X; Xu S; Liu Y; Wang A; Saripan MI; Li L; Zhang X; Lu L
    Cancer Imaging; 2020 Aug; 20(1):53. PubMed ID: 32738913
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Pulmonary nodule detection using hybrid two-stage 3D CNNs.
    Tan M; Wu F; Yang B; Ma J; Kong D; Chen Z; Long D
    Med Phys; 2020 Aug; 47(8):3376-3388. PubMed ID: 32239521
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.
    Eun H; Kim D; Jung C; Kim C
    Comput Methods Programs Biomed; 2018 Oct; 165():215-224. PubMed ID: 30337076
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Evaluation of multislice inputs to convolutional neural networks for medical image segmentation.
    Vu MH; Grimbergen G; Nyholm T; Löfstedt T
    Med Phys; 2020 Dec; 47(12):6216-6231. PubMed ID: 33169365
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs.
    Han G; Liu X; Zheng G; Wang M; Huang S
    Med Biol Eng Comput; 2018 Dec; 56(12):2201-2212. PubMed ID: 29873026
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.
    Rikhari H; Baidya Kayal E; Ganguly S; Sasi A; Sharma S; Dheeksha DS; Saini M; Rangarajan K; Bakhshi S; Kandasamy D; Mehndiratta A
    Int J Comput Assist Radiol Surg; 2024 Feb; 19(2):261-272. PubMed ID: 37594684
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Tumor co-segmentation in PET/CT using multi-modality fully convolutional neural network.
    Zhao X; Li L; Lu W; Tan S
    Phys Med Biol; 2018 Dec; 64(1):015011. PubMed ID: 30523964
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.
    Huang W; Xue Y; Wu Y
    PLoS One; 2019; 14(7):e0219369. PubMed ID: 31299053
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A comparative study of pre-trained convolutional neural networks for semantic segmentation of breast tumors in ultrasound.
    Gómez-Flores W; Coelho de Albuquerque Pereira W
    Comput Biol Med; 2020 Nov; 126():104036. PubMed ID: 33059238
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs.
    Gu Y; Lu X; Yang L; Zhang B; Yu D; Zhao Y; Gao L; Wu L; Zhou T
    Comput Biol Med; 2018 Dec; 103():220-231. PubMed ID: 30390571
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Appraisal of Deep-Learning Techniques on Computer-Aided Lung Cancer Diagnosis with Computed Tomography Screening.
    Agnes SA; Anitha J
    J Med Phys; 2020; 45(2):98-106. PubMed ID: 32831492
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques.
    Apostolopoulos ID; Pintelas EG; Livieris IE; Apostolopoulos DJ; Papathanasiou ND; Pintelas PE; Panayiotakis GS
    Med Biol Eng Comput; 2021 Jun; 59(6):1299-1310. PubMed ID: 34003394
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks.
    Qi Dou ; Hao Chen ; Lequan Yu ; Lei Zhao ; Jing Qin ; Defeng Wang ; Mok VC; Lin Shi ; Pheng-Ann Heng
    IEEE Trans Med Imaging; 2016 May; 35(5):1182-1195. PubMed ID: 26886975
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automatic Segmentation of Multiple Organs on 3D CT Images by Using Deep Learning Approaches.
    Zhou X
    Adv Exp Med Biol; 2020; 1213():135-147. PubMed ID: 32030668
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Fusing 2D and 3D convolutional neural networks for the segmentation of aorta and coronary arteries from CT images.
    Gu L; Cai XC
    Artif Intell Med; 2021 Nov; 121():102189. PubMed ID: 34763804
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automatic lung nodule detection in thoracic CT scans using dilated slice-wise convolutions.
    Farhangi MM; Sahiner B; Petrick N; Pezeshk A
    Med Phys; 2021 Jul; 48(7):3741-3751. PubMed ID: 33932241
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.