Deep learning-based iodine contrast-augmenting algorithm for low-contrast-dose liver CT to assess hypovascular hepatic metastasis.

Journal: Abdominal radiology (New York)

Published Date: Sep 14, 2023

Abstract

PURPOSE: To investigate the image quality and diagnostic performance of low-contrast-dose liver CT using a deep learning-based iodine contrast-augmenting algorithm (DLICA) for hypovascular hepatic metastases.

Authors

Taehee Lee

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Jeong Hee Yoon
Jin Young Park
Jihyuk Lee
Jae Won Choi
Chulkyun Ahn

Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea.
Jeong Min Lee

Keywords

Algorithms Deep Learning Humans Iodine Liver Neoplasms Radiographic Image Interpretation, Computer-Assisted Radiography, Dual-Energy Scanned Projection Retrospective Studies Signal-To-Noise Ratio Tomography, X-Ray Computed

External Resources

View on PubMed Access via DOI PubMed (37704805)

Deep learning-based iodine contrast-augmenting algorithm for low-contrast-dose liver CT to assess hypovascular hepatic metastasis.

Abstract

Authors

Keywords

External Resources

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