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.
334 related articles for article (PubMed ID: 29761358)
1. Deep learning for staging liver fibrosis on CT: a pilot study. Yasaka K; Akai H; Kunimatsu A; Abe O; Kiryu S Eur Radiol; 2018 Nov; 28(11):4578-4585. PubMed ID: 29761358 [TBL] [Abstract][Full Text] [Related]
2. Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid-enhanced Hepatobiliary Phase MR Images. Yasaka K; Akai H; Kunimatsu A; Abe O; Kiryu S Radiology; 2018 Apr; 287(1):146-155. PubMed ID: 29239710 [TBL] [Abstract][Full Text] [Related]
3. Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver. Choi KJ; Jang JK; Lee SS; Sung YS; Shim WH; Kim HS; Yun J; Choi JY; Lee Y; Kang BK; Kim JH; Kim SY; Yu ES Radiology; 2018 Dec; 289(3):688-697. PubMed ID: 30179104 [TBL] [Abstract][Full Text] [Related]
4. Liver fibrosis staging by deep learning: a visual-based explanation of diagnostic decisions of the model. Yin Y; Yakar D; Dierckx RAJO; Mouridsen KB; Kwee TC; de Haas RJ Eur Radiol; 2021 Dec; 31(12):9620-9627. PubMed ID: 34014382 [TBL] [Abstract][Full Text] [Related]
5. Deep residual nets model for staging liver fibrosis on plain CT images. Li Q; Yu B; Tian X; Cui X; Zhang R; Guo Q Int J Comput Assist Radiol Surg; 2020 Aug; 15(8):1399-1406. PubMed ID: 32556922 [TBL] [Abstract][Full Text] [Related]
6. Non-invasive precise staging of liver fibrosis using deep residual network model based on plain CT images. Li Q; Kang H; Zhang R; Guo Q Int J Comput Assist Radiol Surg; 2022 Apr; 17(4):627-637. PubMed ID: 35194737 [TBL] [Abstract][Full Text] [Related]
7. Deep learning with ultrasonography: automated classification of liver fibrosis using a deep convolutional neural network. Lee JH; Joo I; Kang TW; Paik YH; Sinn DH; Ha SY; Kim K; Choi C; Lee G; Yi J; Bang WC Eur Radiol; 2020 Feb; 30(2):1264-1273. PubMed ID: 31478087 [TBL] [Abstract][Full Text] [Related]
8. Radiomics analysis of contrast-enhanced CT for staging liver fibrosis: an update for image biomarker. Wang J; Tang S; Mao Y; Wu J; Xu S; Yue Q; Chen J; He J; Yin Y Hepatol Int; 2022 Jun; 16(3):627-639. PubMed ID: 35347597 [TBL] [Abstract][Full Text] [Related]
9. Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease. Son JH; Lee SS; Lee Y; Kang BK; Sung YS; Jo S; Yu E Eur Radiol; 2020 Jun; 30(6):3486-3496. PubMed ID: 32055946 [TBL] [Abstract][Full Text] [Related]
10. A novel fast kilovoltage switching dual-energy computed tomography technique with deep learning: Utility for non-invasive assessments of liver fibrosis. Wada N; Fujita N; Ishimatsu K; Takao S; Yoshizumi T; Miyazaki Y; Oda Y; Nishie A; Ishigami K; Ushijima Y Eur J Radiol; 2022 Oct; 155():110461. PubMed ID: 35970119 [TBL] [Abstract][Full Text] [Related]
11. Liver fibrosis: noninvasive assessment with MR elastography versus aspartate aminotransferase-to-platelet ratio index. Huwart L; Sempoux C; Salameh N; Jamart J; Annet L; Sinkus R; Peeters F; ter Beek LC; Horsmans Y; Van Beers BE Radiology; 2007 Nov; 245(2):458-66. PubMed ID: 17940304 [TBL] [Abstract][Full Text] [Related]
12. Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI. Hectors SJ; Kennedy P; Huang KH; Stocker D; Carbonell G; Greenspan H; Friedman S; Taouli B Eur Radiol; 2021 Jun; 31(6):3805-3814. PubMed ID: 33201285 [TBL] [Abstract][Full Text] [Related]
14. Radiomics Analysis of Gadoxetic Acid-enhanced MRI for Staging Liver Fibrosis. Park HJ; Lee SS; Park B; Yun J; Sung YS; Shim WH; Shin YM; Kim SY; Lee SJ; Lee MG Radiology; 2019 Feb; 290(2):380-387. PubMed ID: 30615554 [TBL] [Abstract][Full Text] [Related]
15. Diffusion kurtosis imaging with the breath-hold technique for staging hepatic fibrosis: A preliminary study. Yoshimaru D; Miyati T; Suzuki Y; Hamada Y; Mogi N; Funaki A; Tabata A; Masunaga A; Shimada M; Tobari M; Nishino T Magn Reson Imaging; 2018 Apr; 47():33-38. PubMed ID: 29158186 [TBL] [Abstract][Full Text] [Related]
16. A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic hepatitis B. Liu Z; Li W; Zhu Z; Wen H; Li MD; Hou C; Shen H; Huang B; Luo Y; Wang W; Chen X Eur Radiol; 2023 Aug; 33(8):5871-5881. PubMed ID: 36735040 [TBL] [Abstract][Full Text] [Related]
17. Accuracy of liver surface nodularity quantification on MDCT for staging hepatic fibrosis in patients with hepatitis C virus. Lubner MG; Jones D; Said A; Kloke J; Lee S; Pickhardt PJ Abdom Radiol (NY); 2018 Nov; 43(11):2980-2986. PubMed ID: 29572714 [TBL] [Abstract][Full Text] [Related]
18. Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study. Ai H; Huang Y; Tai DI; Tsui PH; Zhou Z Sensors (Basel); 2024 Aug; 24(17):. PubMed ID: 39275424 [TBL] [Abstract][Full Text] [Related]
19. Accuracy of Liver Surface Nodularity Quantification on MDCT as a Noninvasive Biomarker for Staging Hepatic Fibrosis. Pickhardt PJ; Malecki K; Kloke J; Lubner MG AJR Am J Roentgenol; 2016 Dec; 207(6):1194-1199. PubMed ID: 27575867 [TBL] [Abstract][Full Text] [Related]
20. Accuracy of real-time shear wave elastography for assessing liver fibrosis in chronic hepatitis C: a pilot study. Ferraioli G; Tinelli C; Dal Bello B; Zicchetti M; Filice G; Filice C; Hepatology; 2012 Dec; 56(6):2125-33. PubMed ID: 22767302 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]