Content-based medical image retrieval is an important diagnostic tool that improves the explainability of computer-aided diagnosis systems and provides decision making support to healthcare professionals. Medical imaging data, such as radiology images, are often multimorbidity; a single sample may have more than one pathology present. As such, image retrieval systems for the medical domain must be designed for the multi-label scenario. In this paper, we propose a novel multi-label metric learning method that can be used for both classification and content-based image retrieval. In this way, our model is able to support diagnosis by predicting the presence of diseases and provide evidence for these predictions by returning samples with similar pathological content to the user. In practice, the retrieved images may also be accompanied by pathology reports, further assisting in the diagnostic process. Our method leverages proxy feature vectors, enabling the efficient learning of a robust feature space in which the distance between feature vectors can be used as a measure of the similarity of those samples. Unlike existing proxy-based methods, training samples are able to assign to multiple proxies that span multiple class labels. This multi-label proxy assignment results in a feature space that encodes the complex relationships between diseases present in medical imaging data. Our method outperforms state-of-the-art image retrieval systems and a set of baseline approaches. We demonstrate the efficacy of our approach to both classification and content-based image retrieval on two multimorbidity radiology datasets.
翻译:基于内容的医疗图像检索是一个重要的诊断工具,可以改进计算机辅助诊断系统的可解释性,并为医疗专业人员提供决策支持。医学成像数据,如放射图象,往往是多发性;单一样本可能存在不止一种病理病理。因此,医学领域的图像检索系统必须设计为多标签设想方案。在本文件中,我们提出了一个新的多标签衡量指标学习方法,可用于分类和基于内容的图像检索。通过这种方法,我们的模型能够通过将具有类似病理内容的样本退回用户来支持诊断,并为这些预测提供证据。在实践中,所获取的图像还可能附有病理学报告,进一步协助诊断过程。我们的方法利用代理矢量矢量,从而能够有效地学习一个稳健的特性空间,在其中地貌矢量之间的距离可以用来测量这些样品的相似性。与现有的基于代理的分类方法不同,培训样品能够通过将多种类标签的病理存在,为这些预测提供证据。这个多标签代理量图像数据分析方法还配给了我们两个类标签的图像检索系统。这个多标签的多重图像检索方法,我们用来展示了一种复合空间图像模型模型的系统。