BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

117 related articles for article (PubMed ID: 34804142)

  • 1. Adaptive Localizing Region-Based Level Set for Segmentation of Maxillary Sinus Based on Convolutional Neural Networks.
    Qi X; Zhong J; Cui S
    Comput Intell Neurosci; 2021; 2021():4824613. PubMed ID: 34804142
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis.
    Hoogi A; Subramaniam A; Veerapaneni R; Rubin DL
    IEEE Trans Med Imaging; 2017 Mar; 36(3):781-791. PubMed ID: 28113927
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.
    Morgan N; Van Gerven A; Smolders A; de Faria Vasconcelos K; Willems H; Jacobs R
    Sci Rep; 2022 May; 12(1):7523. PubMed ID: 35525857
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automatic liver segmentation by integrating fully convolutional networks into active contour models.
    Guo X; Schwartz LH; Zhao B
    Med Phys; 2019 Oct; 46(10):4455-4469. PubMed ID: 31356688
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Convolutional neural network-based pelvic floor structure segmentation using magnetic resonance imaging in pelvic organ prolapse.
    Feng F; Ashton-Miller JA; DeLancey JOL; Luo J
    Med Phys; 2020 Sep; 47(9):4281-4293. PubMed ID: 32638370
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic CT image segmentation of maxillary sinus based on VGG network and improved V-Net.
    Xu J; Wang S; Zhou Z; Liu J; Jiang X; Chen X
    Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1457-1465. PubMed ID: 32676871
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN.
    Xu X; Zhou F; Liu B
    Int J Comput Assist Radiol Surg; 2018 Jul; 13(7):967-975. PubMed ID: 29556905
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An end-to-end approach to segmentation in medical images with CNN and posterior-CRF.
    Chen S; Sedghi Gamechi Z; Dubost F; van Tulder G; de Bruijne M
    Med Image Anal; 2022 Feb; 76():102311. PubMed ID: 34902793
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Liver tumor segmentation based on 3D convolutional neural network with dual scale.
    Meng L; Tian Y; Bu S
    J Appl Clin Med Phys; 2020 Jan; 21(1):144-157. PubMed ID: 31793212
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks.
    Krüger J; Opfer R; Gessert N; Ostwaldt AC; Manogaran P; Kitzler HH; Schlaefer A; Schippling S
    Neuroimage Clin; 2020; 28():102445. PubMed ID: 33038667
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Efficient skin lesion segmentation using separable-Unet with stochastic weight averaging.
    Tang P; Liang Q; Yan X; Xiang S; Sun W; Zhang D; Coppola G
    Comput Methods Programs Biomed; 2019 Sep; 178():289-301. PubMed ID: 31416556
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Detection, segmentation, and 3D pose estimation of surgical tools using convolutional neural networks and algebraic geometry.
    Hasan MK; Calvet L; Rabbani N; Bartoli A
    Med Image Anal; 2021 May; 70():101994. PubMed ID: 33611053
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Skin Lesion Segmentation with Improved Convolutional Neural Network.
    Öztürk Ş; Özkaya U
    J Digit Imaging; 2020 Aug; 33(4):958-970. PubMed ID: 32378058
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Skin lesion segmentation using high-resolution convolutional neural network.
    Xie F; Yang J; Liu J; Jiang Z; Zheng Y; Wang Y
    Comput Methods Programs Biomed; 2020 Apr; 186():105241. PubMed ID: 31837637
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Convolutional neural network-based approach for segmentation of left ventricle myocardial scar from 3D late gadolinium enhancement MR images.
    Zabihollahy F; White JA; Ukwatta E
    Med Phys; 2019 Apr; 46(4):1740-1751. PubMed ID: 30734937
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.
    Xu M; Qi S; Yue Y; Teng Y; Xu L; Yao Y; Qian W
    Biomed Eng Online; 2019 Jan; 18(1):2. PubMed ID: 30602393
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks.
    Al-Masni MA; Al-Antari MA; Choi MT; Han SM; Kim TS
    Comput Methods Programs Biomed; 2018 Aug; 162():221-231. PubMed ID: 29903489
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Segmentation of dermoscopy images based on deformable 3D convolution and ResU-NeXt +.
    Zhao C; Shuai R; Ma L; Liu W; Wu M
    Med Biol Eng Comput; 2021 Sep; 59(9):1815-1832. PubMed ID: 34304370
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Ischemic Lesion Segmentation using Ensemble of Multi-Scale Region Aligned CNN.
    Karthik R; Menaka R; Hariharan M; Won D
    Comput Methods Programs Biomed; 2021 Mar; 200():105831. PubMed ID: 33223277
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.