BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

148 related articles for article (PubMed ID: 38052145)

  • 1. Deep learning based synthesis of MRI, CT and PET: Review and analysis.
    Dayarathna S; Islam KT; Uribe S; Yang G; Hayat M; Chen Z
    Med Image Anal; 2024 Feb; 92():103046. PubMed ID: 38052145
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep learning for whole-body medical image generation.
    Schaefferkoetter J; Yan J; Moon S; Chan R; Ortega C; Metser U; Berlin A; Veit-Haibach P
    Eur J Nucl Med Mol Imaging; 2021 Nov; 48(12):3817-3826. PubMed ID: 34021779
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Dixon-VIBE Deep Learning (DIVIDE) Pseudo-CT Synthesis for Pelvis PET/MR Attenuation Correction.
    Torrado-Carvajal A; Vera-Olmos J; Izquierdo-Garcia D; Catalano OA; Morales MA; Margolin J; Soricelli A; Salvatore M; Malpica N; Catana C
    J Nucl Med; 2019 Mar; 60(3):429-435. PubMed ID: 30166357
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Medical Image Synthesis via Deep Learning.
    Yu B; Wang Y; Wang L; Shen D; Zhou L
    Adv Exp Med Biol; 2020; 1213():23-44. PubMed ID: 32030661
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space.
    Fallahpoor M; Chakraborty S; Pradhan B; Faust O; Barua PD; Chegeni H; Acharya R
    Comput Methods Programs Biomed; 2024 Jan; 243():107880. PubMed ID: 37924769
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Synthetic CT reconstruction using a deep spatial pyramid convolutional framework for MR-only breast radiotherapy.
    Olberg S; Zhang H; Kennedy WR; Chun J; Rodriguez V; Zoberi I; Thomas MA; Kim JS; Mutic S; Green OL; Park JC
    Med Phys; 2019 Sep; 46(9):4135-4147. PubMed ID: 31309586
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
    Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH
    Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.
    Jiang J; Hu YC; Tyagi N; Zhang P; Rimner A; Deasy JO; Veeraraghavan H
    Med Phys; 2019 Oct; 46(10):4392-4404. PubMed ID: 31274206
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Bidirectional feature matching based on deep pairwise contrastive learning for multiparametric MRI image synthesis.
    Touati R; Kadoury S
    Phys Med Biol; 2023 Jun; 68(12):. PubMed ID: 37257456
    [No Abstract]   [Full Text] [Related]  

  • 10. Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images.
    Li Y; Li W; Xiong J; Xia J; Xie Y
    Biomed Res Int; 2020; 2020():5193707. PubMed ID: 33204701
    [TBL] [Abstract][Full Text] [Related]  

  • 11. [Generation of the Pseudo CT Image Based on the Deep Learning Technique Aimed for the Attenuation Correction of the PET Image].
    Fukui R; Fujii S; Ninomiya H; Fujiwara Y; Ida T
    Nihon Hoshasen Gijutsu Gakkai Zasshi; 2020; 76(11):1152-1162. PubMed ID: 33229845
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI.
    Leynes AP; Yang J; Wiesinger F; Kaushik SS; Shanbhag DD; Seo Y; Hope TA; Larson PEZ
    J Nucl Med; 2018 May; 59(5):852-858. PubMed ID: 29084824
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning-based convolutional neural network for intramodality brain MRI synthesis.
    Osman AFI; Tamam NM
    J Appl Clin Med Phys; 2022 Apr; 23(4):e13530. PubMed ID: 35044073
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep learning based synthetic-CT generation in radiotherapy and PET: A review.
    Spadea MF; Maspero M; Zaffino P; Seco J
    Med Phys; 2021 Nov; 48(11):6537-6566. PubMed ID: 34407209
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep-learning-based methods of attenuation correction for SPECT and PET.
    Chen X; Liu C
    J Nucl Cardiol; 2023 Oct; 30(5):1859-1878. PubMed ID: 35680755
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multimodal image synthesis based on disentanglement representations of anatomical and modality specific features, learned using uncooperative relativistic GAN.
    Reaungamornrat S; Sari H; Catana C; Kamen A
    Med Image Anal; 2022 Aug; 80():102514. PubMed ID: 35717874
    [TBL] [Abstract][Full Text] [Related]  

  • 17. MR-based synthetic CT generation using a deep convolutional neural network method.
    Han X
    Med Phys; 2017 Apr; 44(4):1408-1419. PubMed ID: 28192624
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Strategies for deep learning-based attenuation and scatter correction of brain
    Jahangir R; Kamali-Asl A; Arabi H; Zaidi H
    Med Phys; 2024 Feb; 51(2):870-880. PubMed ID: 38197492
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Augmented deep learning model for improved quantitative accuracy of MR-based PET attenuation correction in PSMA PET-MRI prostate imaging.
    Pozaruk A; Pawar K; Li S; Carey A; Cheng J; Sudarshan VP; Cholewa M; Grummet J; Chen Z; Egan G
    Eur J Nucl Med Mol Imaging; 2021 Jan; 48(1):9-20. PubMed ID: 32394162
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.
    Arabi H; Zeng G; Zheng G; Zaidi H
    Eur J Nucl Med Mol Imaging; 2019 Dec; 46(13):2746-2759. PubMed ID: 31264170
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.