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Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation
Medical Physics ( IF 3.2 ) Pub Date : 2021-07-21 , DOI: 10.1002/mp.15118
Hansang Lee 1 , Haeil Lee 1 , Helen Hong 2 , Heejin Bae 3 , Joon Seok Lim 3 , Junmo Kim 1
Affiliation  

We propose a deep learning method that classifies focal liver lesions (FLLs) into cysts, hemangiomas, and metastases from portal phase abdominal CT images. We propose a synthetic data augmentation process to alleviate the class imbalance and the Lesion INformation Augmented (LINA) patch to improve the learning efficiency.

中文翻译:

使用带有病变信息增强补丁和合成数据增强的卷积神经网络对 CT 图像中的局灶性肝脏病变进行分类

我们提出了一种深度学习方法,该方法可将门静脉期腹部 CT 图像中的局灶性肝脏病变 (FLL) 分类为囊肿、血管瘤和转移瘤。我们提出了一个合成数据增强过程来缓解类不平衡和病变信息增强(LINA)补丁来提高学习效率。
更新日期:2021-09-21
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