论文标题
分解基于内容的图像检索的医学图像的正常和异常特征
Decomposing Normal and Abnormal Features of Medical Images for Content-based Image Retrieval
论文作者
论文摘要
医学图像可以分解为正常和异常特征,这被认为是组成性。基于这个想法,我们提出了一个编码器 - 码头网络将医疗图像分解为两个离散的潜在代码:正常的解剖码和异常解剖码。使用这些潜在代码,我们通过关注医学图像的正常特征或异常特征来证明相似性检索。
Medical images can be decomposed into normal and abnormal features, which is considered as the compositionality. Based on this idea, we propose an encoder-decoder network to decompose a medical image into two discrete latent codes: a normal anatomy code and an abnormal anatomy code. Using these latent codes, we demonstrate a similarity retrieval by focusing on either normal or abnormal features of medical images.