Bergamasco Leila C C, Nunes Fátima L S
Laboratory of Computer Applications for HealthCare, Department of Electrical Engineering - Polytechnic School, University of São Paulo (PPGEE-EP-USP),
AMIA Annu Symp Proc. 2015 Nov 5;2015:1811-20. eCollection 2015.
The increase in volume of medical images generated and stored has created difficulties in accurate image retrieval. An alternative is to generate three-dimensional (3D) models from such medical images and use them in the search. Some of the main cardiac illnesses, such as Congestive Heart Failure (CHF), have deformation in the heart's shape as one of the main symptoms, which can be identified faster in a 3D object than in slices. This article presents techniques developed to retrieve 3D cardiac models using global and local descriptors within a content-based image retrieval system. These techniques were applied in pre-classified 3D models with and without the CHF disease and they were evaluated by using Precision vs. Recall metric. We observed that local descriptors achieved better results than a global descriptor, reaching 85% of accuracy. The results confirmed the potential of using 3D models retrieval in the medical context to aid in the diagnosis.
生成和存储的医学图像数量的增加给准确的图像检索带来了困难。一种替代方法是从这些医学图像生成三维（3D）模型并在搜索中使用它们。一些主要的心脏疾病，如充血性心力衰竭（CHF），其主要症状之一是心脏形状变形，在3D对象中比在切片中能更快地识别出来。本文介绍了在基于内容的图像检索系统中使用全局和局部描述符来检索3D心脏模型的技术。这些技术应用于有或没有CHF疾病的预分类3D模型，并使用精确率与召回率指标进行评估。我们观察到局部描述符比全局描述符取得了更好的结果，准确率达到了85%。结果证实了在医学背景下使用3D模型检索辅助诊断的潜力。
