BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

227 related articles for article (PubMed ID: 36185056)

  • 1. Segmentation of the prostate, its zones, anterior fibromuscular stroma, and urethra on the MRIs and multimodality image fusion using U-Net model.
    Rezaeijo SM; Jafarpoor Nesheli S; Fatan Serj M; Tahmasebi Birgani MJ
    Quant Imaging Med Surg; 2022 Oct; 12(10):4786-4804. PubMed ID: 36185056
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automated segmentation of prostate zonal anatomy on T2-weighted (T2W) and apparent diffusion coefficient (ADC) map MR images using U-Nets.
    Zabihollahy F; Schieda N; Krishna Jeyaraj S; Ukwatta E
    Med Phys; 2019 Jul; 46(7):3078-3090. PubMed ID: 31002381
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Fully automated detection of prostate transition zone tumors on T2-weighted and apparent diffusion coefficient (ADC) map MR images using U-Net ensemble.
    Wong T; Schieda N; Sathiadoss P; Haroon M; Abreu-Gomez J; Ukwatta E
    Med Phys; 2021 Nov; 48(11):6889-6900. PubMed ID: 34418108
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Segmentation of prostate zones using probabilistic atlas-based method with diffusion-weighted MR images.
    Singh D; Kumar V; Das CJ; Singh A; Mehndiratta A
    Comput Methods Programs Biomed; 2020 Nov; 196():105572. PubMed ID: 32544780
    [TBL] [Abstract][Full Text] [Related]  

  • 5. What is the most effective tool for detecting prostate cancer using a standard MR scanner?
    Osugi K; Tanimoto A; Nakashima J; Shinoda K; Hashiguchi A; Oya M; Jinzaki M; Kuribayashi S
    Magn Reson Med Sci; 2013 Dec; 12(4):271-80. PubMed ID: 24172787
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Evaluation of Weighted Diffusion Subtraction for Detection of Clinically Significant Prostate Cancer.
    Sato T; Isoda H; Fujimoto K; Furuta A; Fujimoto M; Ito K; Kobayashi T; Nakamoto Y
    J Magn Reson Imaging; 2021 Dec; 54(6):1979-1988. PubMed ID: 34085328
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation.
    Aldoj N; Biavati F; Dewey M; Hennemuth A; Asbach P; Sack I
    Sci Rep; 2022 Feb; 12(1):2001. PubMed ID: 35132102
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks.
    Lai CC; Wang HK; Wang FN; Peng YC; Lin TP; Peng HH; Shen SH
    Sensors (Basel); 2021 Apr; 21(8):. PubMed ID: 33921451
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep Learning Whole-Gland and Zonal Prostate Segmentation on a Public MRI Dataset.
    Cuocolo R; Comelli A; Stefano A; Benfante V; Dahiya N; Stanzione A; Castaldo A; De Lucia DR; Yezzi A; Imbriaco M
    J Magn Reson Imaging; 2021 Aug; 54(2):452-459. PubMed ID: 33634932
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.
    Chen Y; Xing L; Yu L; Bagshaw HP; Buyyounouski MK; Han B
    Med Phys; 2020 Dec; 47(12):6421-6429. PubMed ID: 33012016
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Relationship between T2 relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume.
    Simpkin CJ; Morgan VA; Giles SL; Riches SF; Parker C; deSouza NM
    Br J Radiol; 2013 Apr; 86(1024):20120469. PubMed ID: 23426849
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Combined model-based and deep learning-based automated 3D zonal segmentation of the prostate on T2-weighted MR images: clinical evaluation.
    Rouvière O; Moldovan PC; Vlachomitrou A; Gouttard S; Riche B; Groth A; Rabotnikov M; Ruffion A; Colombel M; Crouzet S; Weese J; Rabilloud M
    Eur Radiol; 2022 May; 32(5):3248-3259. PubMed ID: 35001157
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Challenge of prostate MRI segmentation on T2-weighted images: inter-observer variability and impact of prostate morphology.
    Montagne S; Hamzaoui D; Allera A; Ezziane M; Luzurier A; Quint R; Kalai M; Ayache N; Delingette H; Renard-Penna R
    Insights Imaging; 2021 Jun; 12(1):71. PubMed ID: 34089410
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fully automated segmentation of prostate whole gland and transition zone in diffusion-weighted MRI using convolutional neural networks.
    Clark T; Zhang J; Baig S; Wong A; Haider MA; Khalvati F
    J Med Imaging (Bellingham); 2017 Oct; 4(4):041307. PubMed ID: 29057288
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Detection and Segmentation of Pelvic Bones Metastases in MRI Images for Patients With Prostate Cancer Based on Deep Learning.
    Liu X; Han C; Cui Y; Xie T; Zhang X; Wang X
    Front Oncol; 2021; 11():773299. PubMed ID: 34912716
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Volumetric and Voxel-Wise Analysis of Dominant Intraprostatic Lesions on Multiparametric MRI.
    Lee J; Carver E; Feldman A; Pantelic MV; Elshaikh M; Wen N
    Front Oncol; 2019; 9():616. PubMed ID: 31334128
    [No Abstract]   [Full Text] [Related]  

  • 17. MRI-based automatic segmentation of rectal cancer using 2D U-Net on two independent cohorts.
    Knuth F; Adde IA; Huynh BN; Groendahl AR; Winter RM; Negård A; Holmedal SH; Meltzer S; Ree AH; Flatmark K; Dueland S; Hole KH; Seierstad T; Redalen KR; Futsaether CM
    Acta Oncol; 2022 Feb; 61(2):255-263. PubMed ID: 34918621
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Dataset of prostate MRI annotated for anatomical zones and cancer.
    Adams LC; Makowski MR; Engel G; Rattunde M; Busch F; Asbach P; Niehues SM; Vinayahalingam S; van Ginneken B; Litjens G; Bressem KK
    Data Brief; 2022 Dec; 45():108739. PubMed ID: 36426089
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Development and acceptability validation of a deep learning-based tool for whole-prostate segmentation on multiparametric MRI: a multicenter study.
    Xu L; Zhang G; Zhang D; Zhang J; Zhang X; Bai X; Chen L; Jin R; Mao L; Li X; Sun H; Jin Z
    Quant Imaging Med Surg; 2023 May; 13(5):3255-3265. PubMed ID: 37179941
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Variability of manual segmentation of the prostate in axial T2-weighted MRI: A multi-reader study.
    Becker AS; Chaitanya K; Schawkat K; Muehlematter UJ; Hötker AM; Konukoglu E; Donati OF
    Eur J Radiol; 2019 Dec; 121():108716. PubMed ID: 31707168
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.