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For: Ahn Y, Yoon JS, Lee SS, Suk HI, Son JH, Sung YS, Lee Y, Kang BK, Kim HS. Deep Learning Algorithm for Automated Segmentation and Volume Measurement of the Liver and Spleen Using Portal Venous Phase Computed Tomography Images. Korean J Radiol 2020;21:987-97. [PMID: 32677383 DOI: 10.3348/kjr.2020.0237] [Cited by in Crossref: 22] [Cited by in F6Publishing: 22] [Article Influence: 11.0] [Reference Citation Analysis]
Number Citing Articles
1 Tajima T, Akai H, Yasaka K, Kunimatsu A, Yamashita Y, Akahane M, Yoshioka N, Abe O, Ohtomo K, Kiryu S. Usefulness of deep learning-based noise reduction for 1.5 T MRI brain images. Clin Radiol 2022:S0009-9260(22)00490-1. [PMID: 36116967 DOI: 10.1016/j.crad.2022.08.127] [Reference Citation Analysis]
2 Choi SJ, Lee SS, Jung KH, Lee JB, Kang HJ, Park HJ, Choi SH, Kim DW, Jang JK. Noncirrhotic Portal Hypertension after Trastuzumab Emtansine in HER2-positive Breast Cancer as Determined by Deep Learning-measured Spleen Volume at CT. Radiology 2022;:220536. [PMID: 35943338 DOI: 10.1148/radiol.220536] [Reference Citation Analysis]
3 Pettit RW, Marlatt BB, Corr SJ, Havelka J, Rana A. nnU-Net Deep Learning Method for Segmenting Parenchyma and Determining Liver Volume From Computed Tomography Images. Annals of Surgery Open 2022;3:e155. [DOI: 10.1097/as9.0000000000000155] [Reference Citation Analysis]
4 Aiello M, Baldi D, Esposito G, Valentino M, Randon M, Salvatore M, Cavaliere C. Evaluation of AI-Based Segmentation Tools for COVID-19 Lung Lesions on Conventional and Ultra-low Dose CT Scans. Dose-Response 2022;20:155932582210828. [DOI: 10.1177/15593258221082896] [Reference Citation Analysis]
5 Wu L, Ning B, Yang J, Chen Y, Zhang C, Yan Y, Koundal D. Diagnosis of Liver Cirrhosis and Liver Fibrosis by Artificial Intelligence Algorithm-Based Multislice Spiral Computed Tomography. Computational and Mathematical Methods in Medicine 2022;2022:1-8. [DOI: 10.1155/2022/1217003] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Park R, Lee S, Sung Y, Yoon J, Suk H, Kim H, Choi S. Accuracy and Efficiency of Right-Lobe Graft Weight Estimation Using Deep-Learning-Assisted CT Volumetry for Living-Donor Liver Transplantation. Diagnostics 2022;12:590. [DOI: 10.3390/diagnostics12030590] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
7 Park SH. Looking Ahead to 2022 for the Korean Journal of Radiology. Korean J Radiol 2022;23:6-9. [PMID: 34983089 DOI: 10.3348/kjr.2021.0844] [Reference Citation Analysis]
8 Meddeb A, Kossen T, Bressem KK, Hamm B, Nagel SN. Evaluation of a Deep Learning Algorithm for Automated Spleen Segmentation in Patients with Conditions Directly or Indirectly Affecting the Spleen. Tomography 2021;7:950-60. [PMID: 34941650 DOI: 10.3390/tomography7040078] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
9 Senkyire IB, Liu Z. Supervised and Semi-supervised Methods for Abdominal Organ Segmentation: A Review. Int J Autom Comput 2021;18:887-914. [DOI: 10.1007/s11633-021-1313-0] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
10 Sugiura A, Treiling L, Al-Kassou B, Shamekhi J, Wilde N, Sinning JM, Zimmer S, Kuetting D, Oldenburg J, Poetzsch B, Nickenig G, Sedaghat A. Spleen Size and Thrombocytopenia After Transcatheter Aortic Valve Implantation. Am J Cardiol 2021;157:85-92. [PMID: 34404506 DOI: 10.1016/j.amjcard.2021.07.021] [Reference Citation Analysis]
11 Qu T, Wang X, Fang C, Mao L, Li J, Li P, Qu J, Li X, Xue H, Yu Y, Jin Z. M3Net: A multi-scale multi-view framework for multi-phase pancreas segmentation based on cross-phase non-local attention. Med Image Anal 2021;75:102232. [PMID: 34700243 DOI: 10.1016/j.media.2021.102232] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
12 Kwon JH, Lee SS, Yoon JS, Suk HI, Sung YS, Kim HS, Lee CM, Kim KM, Lee SJ, Kim SY. Liver-to-Spleen Volume Ratio Automatically Measured on CT Predicts Decompensation in Patients with B Viral Compensated Cirrhosis. Korean J Radiol 2021;22:1985-95. [PMID: 34564961 DOI: 10.3348/kjr.2021.0348] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
13 Su TH, Wu CH, Kao JH. Artificial intelligence in precision medicine in hepatology. J Gastroenterol Hepatol 2021;36:569-80. [PMID: 33709606 DOI: 10.1111/jgh.15415] [Cited by in Crossref: 15] [Cited by in F6Publishing: 18] [Article Influence: 15.0] [Reference Citation Analysis]
14 Sung YS, Park B, Park HJ, Lee SS. Radiomics and deep learning in liver diseases. J Gastroenterol Hepatol 2021;36:561-8. [PMID: 33709608 DOI: 10.1111/jgh.15414] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
15 Kim DW, Ha J, Lee SS, Kwon JH, Kim NY, Sung YS, Yoon JS, Suk HI, Lee Y, Kang BK. Population-based and Personalized Reference Intervals for Liver and Spleen Volumes in Healthy Individuals and Those with Viral Hepatitis. Radiology 2021;:204183. [PMID: 34402668 DOI: 10.1148/radiol.2021204183] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
16 Im WH, Song JS, Jang W. Noninvasive staging of liver fibrosis: review of current quantitative CT and MRI-based techniques. Abdom Radiol (NY) 2021. [PMID: 34228199 DOI: 10.1007/s00261-021-03181-x] [Reference Citation Analysis]
17 Chen J, Ge X, Yang S, He X. Convolutional Neural Networks for Epileptic Disease Detection. 2021 International Conference on Public Health and Data Science (ICPHDS) 2021. [DOI: 10.1109/icphds53608.2021.00026] [Reference Citation Analysis]
18 Tang Y, Zheng Y, Chen X, Wang W, Guo Q, Shu J, Wu J, Su S. Identifying Periampullary Regions in MRI Images Using Deep Learning. Front Oncol 2021;11:674579. [PMID: 34123843 DOI: 10.3389/fonc.2021.674579] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
19 Cardobi N, Dal Palù A, Pedrini F, Beleù A, Nocini R, De Robertis R, Ruzzenente A, Salvia R, Montemezzi S, D'Onofrio M. An Overview of Artificial Intelligence Applications in Liver and Pancreatic Imaging. Cancers (Basel) 2021;13:2162. [PMID: 33946223 DOI: 10.3390/cancers13092162] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
20 Virarkar M, Szklaruk J, Jensen CT, Taggart MW, Bhosale P. What's New in Hepatic Steatosis. Semin Ultrasound CT MR 2021;42:405-15. [PMID: 34130852 DOI: 10.1053/j.sult.2021.03.001] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]