Similar articles for PMID: 30928472

Year	Number of Results
1993	4
1994	2
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2002	1
2004	5
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2014	3
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2022	7
2024	0

1

Artificial intelligence to diagnose meniscus tears on MRI.

Roblot V, Giret Y, Bou Antoun M, Morillot C, Chassin X, Cotten A, Zerbib J, Fournier L. Roblot V, et al. Diagn Interv Imaging. 2019 Apr;100(4):243-249. doi: 10.1016/j.diii.2019.02.007. Epub 2019 Mar 28. Diagn Interv Imaging. 2019. PMID: 30928472 Free article.

2

Automatic knee meniscus tear detection and orientation classification with Mask-RCNN.

Couteaux V, Si-Mohamed S, Nempont O, Lefevre T, Popoff A, Pizaine G, Villain N, Bloch I, Cotten A, Boussel L. Couteaux V, et al. Diagn Interv Imaging. 2019 Apr;100(4):235-242. doi: 10.1016/j.diii.2019.03.002. Epub 2019 Mar 23. Diagn Interv Imaging. 2019. PMID: 30910620 Free article.

3

Development of convolutional neural network model for diagnosing meniscus tear using magnetic resonance image.

Shin H, Choi GS, Shon OJ, Kim GB, Chang MC. Shin H, et al. BMC Musculoskelet Disord. 2022 May 30;23(1):510. doi: 10.1186/s12891-022-05468-6. BMC Musculoskelet Disord. 2022. PMID: 35637451 Free PMC article.

4

Identification and diagnosis of meniscus tear by magnetic resonance imaging using a deep learning model.

Li J, Qian K, Liu J, Huang Z, Zhang Y, Zhao G, Wang H, Li M, Liang X, Zhou F, Yu X, Li L, Wang X, Yang X, Jiang Q. Li J, et al. J Orthop Translat. 2022 Jun 26;34:91-101. doi: 10.1016/j.jot.2022.05.006. eCollection 2022 May. J Orthop Translat. 2022. PMID: 35847603 Free PMC article.

5

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.

Bien N, Rajpurkar P, Ball RL, Irvin J, Park A, Jones E, Bereket M, Patel BN, Yeom KW, Shpanskaya K, Halabi S, Zucker E, Fanton G, Amanatullah DF, Beaulieu CF, Riley GM, Stewart RJ, Blankenberg FG, Larson DB, Jones RH, Langlotz CP, Ng AY, Lungren MP. Bien N, et al. PLoS Med. 2018 Nov 27;15(11):e1002699. doi: 10.1371/journal.pmed.1002699. eCollection 2018 Nov. PLoS Med. 2018. PMID: 30481176 Free PMC article.

6

Automated meniscus segmentation and tear detection of knee MRI with a 3D mask-RCNN.

Li YZ, Wang Y, Fang KB, Zheng HZ, Lai QQ, Xia YF, Chen JY, Dai ZS. Li YZ, et al. Eur J Med Res. 2022 Nov 14;27(1):247. doi: 10.1186/s40001-022-00883-w. Eur J Med Res. 2022. PMID: 36372871 Free PMC article.

7

Meniscal lesion detection and characterization in adult knee MRI: A deep learning model approach with external validation.

Rizk B, Brat H, Zille P, Guillin R, Pouchy C, Adam C, Ardon R, d'Assignies G. Rizk B, et al. Phys Med. 2021 Mar;83:64-71. doi: 10.1016/j.ejmp.2021.02.010. Epub 2021 Mar 11. Phys Med. 2021. PMID: 33714850

8

[Diagnostic value of MRI for posterior root tear of medial and lateral meniscus].

Qian YN, Liu F, Dong YL, Cai CY. Qian YN, et al. Zhongguo Gu Shang. 2018 Mar 25;31(3):263-266. doi: 10.3969/j.issn.1003-0034.2018.03.014. Zhongguo Gu Shang. 2018. PMID: 29600679 Chinese.

9

A Multi-Task Deep Learning Method for Detection of Meniscal Tears in MRI Data from the Osteoarthritis Initiative Database.

Tack A, Shestakov A, Lüdke D, Zachow S. Tack A, et al. Front Bioeng Biotechnol. 2021 Dec 2;9:747217. doi: 10.3389/fbioe.2021.747217. eCollection 2021. Front Bioeng Biotechnol. 2021. PMID: 34926416 Free PMC article.

10

[Magnetic resonance imaging of medial meniscus tears with displaced fragment in the meniscal recesses].

Le Hir P, Charousset C, Duranthon LD, Grimberg J, Schmider L, Elis JB, Chassaing V, Laude F. Le Hir P, et al. Rev Chir Orthop Reparatrice Appar Mot. 2007 Jun;93(4):357-63. doi: 10.1016/s0035-1040(07)90277-9. Rev Chir Orthop Reparatrice Appar Mot. 2007. PMID: 17646817 French.

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