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Updated: May 6, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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基于混合的数据增强的班级智能的组合,用于学习腹部CT图像中的肝脏焦点损伤的班级失衡

Hansang Lee1, Deokseon Kim2, Joonseok Lim3

  • 1School of Electrical Engineering, KAIST, Daehark 291, Yuseonggu, Daejeon, 34141, Republic of Korea.

Journal of imaging informatics in medicine
|January 27, 2025
PubMed
概括

这项研究引入了一种新的数据增强方法,以改善CT扫描中焦点肝病变 (FLL) 的分类. 基于混合的数据增强 (CCDA) 的类明智组合提高了识别罕见FLL类型的准确性.

关键词:
在AugMix中,我们可以使用AugMix.分类 分类 分类 分类.数据增强数据增强肝脏的焦点病变是肝脏的焦点病变.这是一个MixUp MixUp.

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Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
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