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 *

99 related articles for article (PubMed ID: 37221711)

  • 41. A geometry-guided multi-beamlet deep learning technique for CT reconstruction.
    Lu K; Ren L; Yin FF
    Biomed Phys Eng Express; 2022 May; 8(4):. PubMed ID: 35512654
    [No Abstract]   [Full Text] [Related]  

  • 42. Dual-consistency semi-supervision combined with self-supervision for vessel segmentation in retinal OCTA images.
    Chen Z; Xiong Y; Wei H; Zhao R; Duan X; Shen H
    Biomed Opt Express; 2022 May; 13(5):2824-2834. PubMed ID: 35774329
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Approximating the uncertainty of deep learning reconstruction predictions in single-pixel imaging.
    Shang R; O'Brien MA; Wang F; Situ G; Luke GP
    Commun Eng; 2023; 2():. PubMed ID: 38463559
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Phase retrieval with physics informed zero-shot network.
    Kumar S
    Opt Lett; 2021 Dec; 46(23):5942-5945. PubMed ID: 34851929
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Deep compressed sensing MRI via a gradient-enhanced fusion model.
    Dai Y; Wang C; Wang H
    Med Phys; 2023 Mar; 50(3):1390-1405. PubMed ID: 36695158
    [TBL] [Abstract][Full Text] [Related]  

  • 46. MeshLifter: Weakly Supervised Approach for 3D Human Mesh Reconstruction from a Single 2D Pose Based on Loop Structure.
    Jeong S; Chang JY
    Sensors (Basel); 2020 Jul; 20(15):. PubMed ID: 32751645
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Experimental comparison of single-pixel imaging algorithms.
    Bian L; Suo J; Dai Q; Chen F
    J Opt Soc Am A Opt Image Sci Vis; 2018 Jan; 35(1):78-87. PubMed ID: 29328095
    [TBL] [Abstract][Full Text] [Related]  

  • 48. A semi-supervised learning method of latent features based on convolutional neural networks for CT metal artifact reduction.
    Shi Z; Wang N; Kong F; Cao H; Cao Q
    Med Phys; 2022 Jun; 49(6):3845-3859. PubMed ID: 35322430
    [TBL] [Abstract][Full Text] [Related]  

  • 49. SpiNet: A deep neural network for Schatten p-norm regularized medical image reconstruction.
    Rastogi A; Yalavarthy PK
    Med Phys; 2021 May; 48(5):2214-2229. PubMed ID: 33525049
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Image-based shading correction for narrow-FOV truncated pelvic CBCT with deep convolutional neural networks and transfer learning.
    Rossi M; Belotti G; Paganelli C; Pella A; Barcellini A; Cerveri P; Baroni G
    Med Phys; 2021 Nov; 48(11):7112-7126. PubMed ID: 34636429
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Self-supervised learning for remote sensing scene classification under the few shot scenario.
    Alosaimi N; Alhichri H; Bazi Y; Ben Youssef B; Alajlan N
    Sci Rep; 2023 Jan; 13(1):433. PubMed ID: 36624136
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Deep-learning-based projection-domain breast thickness estimation for shape-prior iterative image reconstruction in digital breast tomosynthesis.
    Lee S; Kim H; Lee H; Cho S
    Med Phys; 2022 Jun; 49(6):3670-3682. PubMed ID: 35297075
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Deep learning based spectral extrapolation for dual-source, dual-energy x-ray computed tomography.
    Clark DP; Schwartz FR; Marin D; Ramirez-Giraldo JC; Badea CT
    Med Phys; 2020 Sep; 47(9):4150-4163. PubMed ID: 32531114
    [TBL] [Abstract][Full Text] [Related]  

  • 54. An Efficient Light-weight Network for Fast Reconstruction on MR Images.
    Zhen B; Zheng Y; Qiu B
    Curr Med Imaging; 2021; 17(11):1374-1384. PubMed ID: 33459243
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Deep learning based projector defocus compensation in single-pixel imaging.
    Rizvi S; Cao J; Hao Q
    Opt Express; 2020 Aug; 28(17):25134-25148. PubMed ID: 32907042
    [TBL] [Abstract][Full Text] [Related]  

  • 56. X-ray Cherenkov-luminescence tomography reconstruction with a three-component deep learning algorithm: Swin transformer, convolutional neural network, and locality module.
    Feng J; Zhang H; Geng M; Chen H; Jia K; Sun Z; Li Z; Cao X; Pogue BW
    J Biomed Opt; 2023 Feb; 28(2):026004. PubMed ID: 36818584
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Deep self-supervised transformation learning for leukocyte classification.
    Chen X; Zheng G; Zhou L; Li Z; Fan H
    J Biophotonics; 2023 Mar; 16(3):e202200244. PubMed ID: 36377387
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Dual-domain accelerated MRI reconstruction using transformers with learning-based undersampling.
    Hong GQ; Wei YT; Morley WAW; Wan M; Mertens AJ; Su Y; Cheng HM
    Comput Med Imaging Graph; 2023 Jun; 106():102206. PubMed ID: 36857952
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Learning CT projection denoising from adjacent views.
    Hong Z; Zeng D; Tao X; Ma J
    Med Phys; 2023 Mar; 50(3):1367-1377. PubMed ID: 36414024
    [TBL] [Abstract][Full Text] [Related]  

  • 60. An encoder-decoder network for direct image reconstruction on sinograms of a long axial field of view PET.
    Ma R; Hu J; Sari H; Xue S; Mingels C; Viscione M; Kandarpa VSS; Li WB; Visvikis D; Qiu R; Rominger A; Li J; Shi K
    Eur J Nucl Med Mol Imaging; 2022 Nov; 49(13):4464-4477. PubMed ID: 35819497
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 5.