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 *

504 related articles for article (PubMed ID: 32594208)

  • 1. 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]  

  • 2. Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.
    Aldoj N; Lukas S; Dewey M; Penzkofer T
    Eur Radiol; 2020 Feb; 30(2):1243-1253. PubMed ID: 31468158
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.
    Song Y; Zhang YD; Yan X; Liu H; Zhou M; Hu B; Yang G
    J Magn Reson Imaging; 2018 Dec; 48(6):1570-1577. PubMed ID: 29659067
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.
    Yang X; Liu C; Wang Z; Yang J; Min HL; Wang L; Cheng KT
    Med Image Anal; 2017 Dec; 42():212-227. PubMed ID: 28850876
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features.
    Bernatz S; Ackermann J; Mandel P; Kaltenbach B; Zhdanovich Y; Harter PN; Döring C; Hammerstingl R; Bodelle B; Smith K; Bucher A; Albrecht M; Rosbach N; Basten L; Yel I; Wenzel M; Bankov K; Koch I; Chun FK; Köllermann J; Wild PJ; Vogl TJ
    Eur Radiol; 2020 Dec; 30(12):6757-6769. PubMed ID: 32676784
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Computer-aided diagnosis of prostate cancer on magnetic resonance imaging using a convolutional neural network algorithm.
    Ishioka J; Matsuoka Y; Uehara S; Yasuda Y; Kijima T; Yoshida S; Yokoyama M; Saito K; Kihara K; Numao N; Kimura T; Kudo K; Kumazawa I; Fujii Y
    BJU Int; 2018 Sep; 122(3):411-417. PubMed ID: 29772101
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Multiparametric MRI-ultrasonography software fusion prostate biopsy: initial results using a stereotactic robotic-assisted transperineal prostate biopsy platform comparing systematic vs targeted biopsy.
    Lee AYM; Yang XY; Lee HJ; Law YM; Huang HH; Lau WKO; Lee LS; Ho HSS; Tay KJ; Cheng CWS; Yuen JSP; Chen K
    BJU Int; 2020 Nov; 126(5):568-576. PubMed ID: 32438463
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Cascaded Deep Learning-Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging.
    Mehralivand S; Yang D; Harmon SA; Xu D; Xu Z; Roth H; Masoudi S; Sanford TH; Kesani D; Lay NS; Merino MJ; Wood BJ; Pinto PA; Choyke PL; Turkbey B
    Acad Radiol; 2022 Aug; 29(8):1159-1168. PubMed ID: 34598869
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Using decision curve analysis to benchmark performance of a magnetic resonance imaging-based deep learning model for prostate cancer risk assessment.
    Deniffel D; Abraham N; Namdar K; Dong X; Salinas E; Milot L; Khalvati F; Haider MA
    Eur Radiol; 2020 Dec; 30(12):6867-6876. PubMed ID: 32591889
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An integrated nomogram combining deep learning, Prostate Imaging-Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study.
    Hiremath A; Shiradkar R; Fu P; Mahran A; Rastinehad AR; Tewari A; Tirumani SH; Purysko A; Ponsky L; Madabhushi A
    Lancet Digit Health; 2021 Jul; 3(7):e445-e454. PubMed ID: 34167765
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prostate cancer heterogeneity: texture analysis score based on multiple magnetic resonance imaging sequences for detection, stratification and selection of lesions at time of biopsy.
    Orczyk C; Villers A; Rusinek H; Lepennec V; Bazille C; Giganti F; Mikheev A; Bernaudin M; Emberton M; Fohlen A; Valable S
    BJU Int; 2019 Jul; 124(1):76-86. PubMed ID: 30378238
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 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. Application of a validated prostate MRI deep learning system to independent same-vendor multi-institutional data: demonstration of transferability.
    Netzer N; Eith C; Bethge O; Hielscher T; Schwab C; Stenzinger A; Gnirs R; Schlemmer HP; Maier-Hein KH; Schimmöller L; Bonekamp D
    Eur Radiol; 2023 Nov; 33(11):7463-7476. PubMed ID: 37507610
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment.
    Schelb P; Wang X; Radtke JP; Wiesenfarth M; Kickingereder P; Stenzinger A; Hohenfellner M; Schlemmer HP; Maier-Hein KH; Bonekamp D
    Eur Radiol; 2021 Jan; 31(1):302-313. PubMed ID: 32767102
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Combined Transfer Learning and Test-Time Augmentation Improves Convolutional Neural Network-Based Semantic Segmentation of Prostate Cancer from Multi-Parametric MR Images.
    Hoar D; Lee PQ; Guida A; Patterson S; Bowen CV; Merrimen J; Wang C; Rendon R; Beyea SD; Clarke SE
    Comput Methods Programs Biomed; 2021 Oct; 210():106375. PubMed ID: 34500139
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Multiparametric MRI in detection and staging of prostate cancer.
    Boesen L
    Dan Med J; 2017 Feb; 64(2):. PubMed ID: 28157066
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep learning-assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge.
    Hosseinzadeh M; Saha A; Brand P; Slootweg I; de Rooij M; Huisman H
    Eur Radiol; 2022 Apr; 32(4):2224-2234. PubMed ID: 34786615
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Assessment of PI-RADS v2 categories ≥ 3 for diagnosis of clinically significant prostate cancer.
    Patel NU; Lind KE; Garg K; Crawford D; Werahera PN; Pokharel SS
    Abdom Radiol (NY); 2019 Feb; 44(2):705-712. PubMed ID: 30171296
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 26.