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Thermal Medical Image Retrieval by Moment Invariants

机译:通过矩不变量检索热医学图像

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Thermal medical imaging provides a valuable method for detecting various diseases such as breast cancer or Raynaud's syndrome. While previous efforts on the automated processing on thermal infrared images were designed for and hence constrained to a certain type of disease we apply the concept of content-based image retrieval (CBIR) as a more generic approach to the problem. CBIR allows the retrieval of similar images based on features extracted directly from image data. Image retrieval for a thermal image that shows symptoms of a certain disease will provide visually similar cases which usually also represent similarities in medical terms. The image features we investigate in this study are a set of combinations of geometric image moments which are invariant to translation, scale, rotation and contrast.
机译:热医学成像为检测各种疾病(例如乳腺癌或雷诺氏综合症)提供了一种有价值的方法。尽管先前针对热红外图像进行自动处理的工作是针对某种疾病而设计的,但因此仅限于某种疾病,但我们将基于内容的图像检索(CBIR)的概念作为解决该问题的通用方法。 CBIR允许基于直接从图像数据中提取的特征来检索相似图像。对于显示某种疾病症状的热图像进行图像检索,将提供视觉上相似的病例,通常在医学上也代表相似之处。我们在这项研究中研究的图像特征是一组几何图像矩的组合,这些矩对平移,缩放,旋转和对比度不变。

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