- Prediction of Decompensation and Death in Advanced Chronic Liver Disease Using Deep Learning Analysis of Gadoxetic Acid-Enhanced MRI
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Heo S, Lee SS, Kim SY, Lim YS, Park HJ, Yoon JS, Suk HI, Sung YS, Park B, Lee JS
- KMID: 2536344
- Korean J Radiol.
- 2022 Dec;23(12):1269-1280.
- doi: 10.3348/kjr.2022.0494
Objective: This study aimed to evaluate the usefulness of quantitative indices obtained from deep learning analysis of gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and their longitudinal changes in predicting decompensation... -
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- Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI
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Park HJ, Yoon JS, Lee SS, Suk HI, Park B, Sung YS, Hong SB, Ryu H
- KMID: 2530757
- Korean J Radiol.
- 2022 Jul;23(7):720-731.
- doi: 10.3348/kjr.2021.0892
Objective: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic... -
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- Deep Learning Algorithm for Automated Segmentationand Volume Measurement of the Liver and Spleen UsingPortal Venous Phase Computed Tomography Images
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Ahn Y, Yoon JS, Lee SS, Suk HI, Son JH, Sung YS, Lee Y, Kang BK, Kim HS
- KMID: 2505137
- Korean J Radiol.
- 2020 Aug;21(8):987-997.
- doi: 10.3348/kjr.2020.0237
Objective: Measurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT)volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement,... -
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