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Deep Learning Algorithm for Automated Segmentationand Volume Measurement of the Liver and Spleen UsingPortal Venous Phase Computed Tomography Images

Ahn Y, Yoon JS, Lee SS, Suk HI, Son JH, Sung YS, Lee Y, Kang BK, Kim HS

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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Liver-to-Spleen Volume Ratio Automatically Measured on CT Predicts Decompensation in Patients with B Viral Compensated Cirrhosis

Kwon JH, Lee SS, Yoon JS, Suk HI, Sung YS, Kim HS, Lee Cm, Kim KM, Lee SJ, Kim SY

Objective: Although the liver-to-spleen volume ratio (LSVR) based on CT reflects portal hypertension, its prognostic role in cirrhotic patients has not been proven. We evaluated the utility of LSVR, automatically...
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Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI

Park HJ, Yoon JS, Lee SS, Suk HI, Park B, Sung YS, Hong SB, Ryu H

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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Prediction of Decompensation and Death in Advanced Chronic Liver Disease Using Deep Learning Analysis of Gadoxetic Acid-Enhanced MRI

Heo S, Lee SS, Kim SY, Lim YS, Park HJ, Yoon JS, Suk HI, Sung YS, Park B, Lee JS

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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