These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

769 related articles for article (PubMed ID: 31319957)

  • 1. An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.
    Souza JC; Bandeira Diniz JO; Ferreira JL; França da Silva GL; Corrêa Silva A; de Paiva AC
    Comput Methods Programs Biomed; 2019 Aug; 177():285-296. PubMed ID: 31319957
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Contour-aware multi-label chest X-ray organ segmentation.
    Kholiavchenko M; Sirazitdinov I; Kubrak K; Badrutdinova R; Kuleev R; Yuan Y; Vrtovec T; Ibragimov B
    Int J Comput Assist Radiol Surg; 2020 Mar; 15(3):425-436. PubMed ID: 32034633
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. H-SegNet: hybrid segmentation network for lung segmentation in chest radiographs using mask region-based convolutional neural network and adaptive closed polyline searching method.
    Peng T; Wang C; Zhang Y; Wang J
    Phys Med Biol; 2022 Mar; 67(7):. PubMed ID: 35287125
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Digital hair segmentation using hybrid convolutional and recurrent neural networks architecture.
    Attia M; Hossny M; Zhou H; Nahavandi S; Asadi H; Yazdabadi A
    Comput Methods Programs Biomed; 2019 Aug; 177():17-30. PubMed ID: 31319945
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of the automatic segmentation of multiple organs at risk in CT images of lung cancer between deep convolutional neural network-based and atlas-based techniques.
    Zhu J; Zhang J; Qiu B; Liu Y; Liu X; Chen L
    Acta Oncol; 2019 Feb; 58(2):257-264. PubMed ID: 30398090
    [TBL] [Abstract][Full Text] [Related]  

  • 7. MDU-Net: A Convolutional Network for Clavicle and Rib Segmentation from a Chest Radiograph.
    Wang W; Feng H; Bu Q; Cui L; Xie Y; Zhang A; Feng J; Zhu Z; Chen Z
    J Healthc Eng; 2020; 2020():2785464. PubMed ID: 32724504
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Kidney segmentation from computed tomography images using deep neural network.
    da Cruz LB; Araújo JDL; Ferreira JL; Diniz JOB; Silva AC; de Almeida JDS; de Paiva AC; Gattass M
    Comput Biol Med; 2020 Aug; 123():103906. PubMed ID: 32768047
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.
    Xie Y; Wu Z; Han X; Wang H; Wu Y; Cui L; Feng J; Zhu Z; Chen Z
    J Healthc Eng; 2020; 2020():9205082. PubMed ID: 32908660
    [TBL] [Abstract][Full Text] [Related]  

  • 10. RPLS-Net: pulmonary lobe segmentation based on 3D fully convolutional networks and multi-task learning.
    Liu J; Wang C; Guo J; Shao J; Xu X; Liu X; Li H; Li W; Yi Z
    Int J Comput Assist Radiol Surg; 2021 Jun; 16(6):895-904. PubMed ID: 33846890
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computer-aided diagnosis of pulmonary diseases using x-ray darkfield radiography.
    Einarsdóttir H; Yaroshenko A; Velroyen A; Bech M; Hellbach K; Auweter S; Yildirim Ö; Meinel FG; Eickelberg O; Reiser M; Larsen R; Ersbøll BK; Pfeiffer F
    Phys Med Biol; 2015 Dec; 60(24):9253-68. PubMed ID: 26577057
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Fully Convolutional Architectures for Multiclass Segmentation in Chest Radiographs.
    Novikov AA; Lenis D; Major D; Hladuvka J; Wimmer M; Buhler K
    IEEE Trans Med Imaging; 2018 Aug; 37(8):1865-1876. PubMed ID: 29994439
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images.
    Yahyatabar M; Jouvet P; Cheriet F
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1242-1245. PubMed ID: 33018212
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Small lung nodules detection based on local variance analysis and probabilistic neural network.
    Woźniak M; Połap D; Capizzi G; Sciuto GL; Kośmider L; Frankiewicz K
    Comput Methods Programs Biomed; 2018 Jul; 161():173-180. PubMed ID: 29852959
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Lung Region Segmentation in Chest X-Ray Images using Deep Convolutional Neural Networks.
    Portela RDS; Pereira JRG; Costa MGF; Filho CFFC
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1246-1249. PubMed ID: 33018213
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Gradient vector flow based active shape model for lung field segmentation in chest radiographs.
    Xu T; Mandal M; Long R; Basu A
    Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():3561-4. PubMed ID: 19964999
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming.
    Maduskar P; Hogeweg L; de Jong PA; Peters-Bax L; Dawson R; Ayles H; Sánchez CI; van Ginneken B
    Med Phys; 2014 Jul; 41(7):071912. PubMed ID: 24989390
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Extracting Lungs from CT Images via Deep Convolutional Neural Network Based Segmentation and Two-Pass Contour Refinement.
    Liu C; Pang M
    J Digit Imaging; 2020 Dec; 33(6):1465-1478. PubMed ID: 33057882
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images.
    Naceur MB; Saouli R; Akil M; Kachouri R
    Comput Methods Programs Biomed; 2018 Nov; 166():39-49. PubMed ID: 30415717
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A review on lung boundary detection in chest X-rays.
    Candemir S; Antani S
    Int J Comput Assist Radiol Surg; 2019 Apr; 14(4):563-576. PubMed ID: 30730032
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 39.