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Pathology-centric medical image retrieval with hierarchical contextual spatial descriptor

机译:具有分层上下文空间描述符的以病理学为中心的医学图像检索

摘要

Content-based image retrieval has been suggested as an aid to medical diagnosis. Techniques based on standard feature descriptors, however, might not represent optimally the pathological characteristics in medical images. In this paper, we propose a new approach for medical image retrieval based on pathology-centric feature extraction and representation; and patch-based local feature extraction and hierarchical contextual spatial descriptor are designed. The proposed method is evaluated on positron emission tomography - computed tomography (PET-CT) images from subjects with non-small cell lung cancer (NSCLC), showing promising performance improvements over the other benchmarked techniques.
机译:已经提出基于内容的图像检索作为医学诊断的辅助手段。但是,基于标准特征描述符的技术可能无法最佳地代表医学图像中的病理特征。本文提出了一种基于病理学特征提取和表示的医学图像检索新方法。设计了基于补丁的局部特征提取和分层上下文空间描述符。在来自非小细胞肺癌(NSCLC)受试者的正电子发射断层扫描-计算机断层扫描(PET-CT)图像上对提出的方法进行了评估,与其他基准技术相比,该方法显示出令人鼓舞的性能。

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