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Updated: Jan 13, 2026

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
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ClinReadNet:一个以临床阅读为灵感的网络,用于低剂量腹部CT图像质量评估

Xianye Xiao1, Yulong Zou1, Yujie Luo1

  • 1School of Mathematics and Computer Sciences, Nanchang University, Nanchang 330031, China; School of Information Engineering, Nanchang University, Nanchang 330031, China.

Neural networks : the official journal of the International Neural Network Society
|January 6, 2026
PubMed
概括

一个新的深度学习模型,ClinReadNet,准确地评估腹部CT图像质量,没有参考. 这种无参考图像质量评估 (无参考IQA) 工具模仿放射科医生,提高效率并保持低剂量扫描中的诊断准确性.

关键词:
临床阅读逻辑的临床阅读逻辑深度学习是一种深度学习.图像质量评估 (IQA) 是指图像质量的评估.低剂量的CT图像没有参考的IQA

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