BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

357 related articles for article (PubMed ID: 36690774)

  • 1. Automated prostate multi-regional segmentation in magnetic resonance using fully convolutional neural networks.
    Jimenez-Pastor A; Lopez-Gonzalez R; Fos-Guarinos B; Garcia-Castro F; Wittenberg M; Torregrosa-Andrés A; Marti-Bonmati L; Garcia-Fontes M; Duarte P; Gambini JP; Bittencourt LK; Kitamura FC; Venugopal VK; Mahajan V; Ros P; Soria-Olivas E; Alberich-Bayarri A
    Eur Radiol; 2023 Jul; 33(7):5087-5096. PubMed ID: 36690774
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fully automatic segmentation on prostate MR images based on cascaded fully convolution network.
    Zhu Y; Wei R; Gao G; Ding L; Zhang X; Wang X; Zhang J
    J Magn Reson Imaging; 2019 Apr; 49(4):1149-1156. PubMed ID: 30350434
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 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. 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]  

  • 6. Prostate cancer detection and segmentation on MRI using non-local mask R-CNN with histopathological ground truth.
    Dai Z; Jambor I; Taimen P; Pantelic M; Elshaikh M; Dabaja A; Rogers C; Ettala O; Boström PJ; Aronen HJ; Merisaari H; Wen N
    Med Phys; 2023 Dec; 50(12):7748-7763. PubMed ID: 37358061
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Segmentation of the Prostate Transition Zone and Peripheral Zone on MR Images with Deep Learning.
    Bardis M; Houshyar R; Chantaduly C; Tran-Harding K; Ushinsky A; Chahine C; Rupasinghe M; Chow D; Chang P
    Radiol Imaging Cancer; 2021 May; 3(3):e200024. PubMed ID: 33929265
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
    Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
    Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Deeply supervised 3D fully convolutional networks with group dilated convolution for automatic MRI prostate segmentation.
    Wang B; Lei Y; Tian S; Wang T; Liu Y; Patel P; Jani AB; Mao H; Curran WJ; Liu T; Yang X
    Med Phys; 2019 Apr; 46(4):1707-1718. PubMed ID: 30702759
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.
    Kawula M; Hadi I; Nierer L; Vagni M; Cusumano D; Boldrini L; Placidi L; Corradini S; Belka C; Landry G; Kurz C
    Med Phys; 2023 Mar; 50(3):1573-1585. PubMed ID: 36259384
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of automated segmentation techniques for magnetic resonance images of the prostate.
    Isaksson LJ; Pepa M; Summers P; Zaffaroni M; Vincini MG; Corrao G; Mazzola GC; Rotondi M; Lo Presti G; Raimondi S; Gandini S; Volpe S; Haron Z; Alessi S; Pricolo P; Mistretta FA; Luzzago S; Cattani F; Musi G; Cobelli O; Cremonesi M; Orecchia R; Marvaso G; Petralia G; Jereczek-Fossa BA
    BMC Med Imaging; 2023 Feb; 23(1):32. PubMed ID: 36774463
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on Magnetic Resonance Imaging for Targeted Biopsy.
    Soerensen SJC; Fan RE; Seetharaman A; Chen L; Shao W; Bhattacharya I; Kim YH; Sood R; Borre M; Chung BI; To'o KJ; Rusu M; Sonn GA
    J Urol; 2021 Sep; 206(3):604-612. PubMed ID: 33878887
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Segmentation of prostate and prostate zones using deep learning : A multi-MRI vendor analysis.
    Zavala-Romero O; Breto AL; Xu IR; Chang YC; Gautney N; Dal Pra A; Abramowitz MC; Pollack A; Stoyanova R
    Strahlenther Onkol; 2020 Oct; 196(10):932-942. PubMed ID: 32221622
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Explainable AI for CNN-based prostate tumor segmentation in multi-parametric MRI correlated to whole mount histopathology.
    Gunashekar DD; Bielak L; Hägele L; Oerther B; Benndorf M; Grosu AL; Brox T; Zamboglou C; Bock M
    Radiat Oncol; 2022 Apr; 17(1):65. PubMed ID: 35366918
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Clinically significant prostate cancer detection and segmentation in low-risk patients using a convolutional neural network on multi-parametric MRI.
    Arif M; Schoots IG; Castillo Tovar J; Bangma CH; Krestin GP; Roobol MJ; Niessen W; Veenland JF
    Eur Radiol; 2020 Dec; 30(12):6582-6592. PubMed ID: 32594208
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. 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]  

  • 20. Three-Dimensional Convolutional Neural Network for Prostate MRI Segmentation and Comparison of Prostate Volume Measurements by Use of Artificial Neural Network and Ellipsoid Formula.
    Lee DK; Sung DJ; Kim CS; Heo Y; Lee JY; Park BJ; Kim MJ
    AJR Am J Roentgenol; 2020 Jun; 214(6):1229-1238. PubMed ID: 32208009
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 18.