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Case Based Image Retrieval and Clinical Analysis of Tumor and Cyst

机译：基于案例的肿瘤和囊肿图像检索与临床分析

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Case based reasoning (CBR) with image retrieval can be used to implement a clinical decision support systemfor supporting diagnosis of space occupying lesions . We present a Case Based Image Retrieval (CBIR) system toretrieve images with lesion similar to the input test image. Here we consider only Glioblasoma and lung cancerlesions. The lung cancer lesions can be either nodules or cysts. A feature database has been created and theprocessing of a query is conducted in real time. By using Bag of visual words (BOVW), histogram of features iscompared with the codebook to retrieve similar images.The experiments performed at various levels retrieved relevant and similar images of lesion images with amean average precision of 0.85. The system presented is expected aid and improve the e ectiveness of diagnosisperformed by radiologist.

机译：基于案例的推理（CBR）具有图像检索可用于实施临床决策支持系统用于支持占据占据病变的空间的诊断。我们介绍基于案例的图像检索（CBIR）系统检索具有类似输入测试图像的病变的图像。在这里，我们只考虑胶质毛纹瘤和肺癌病变。肺癌病变可以是结节或囊肿。已创建一个功能数据库和查询的处理实时进行。通过使用一袋视觉单词（BOVW），功能的直方图是与码本相比检索类似图像。在各个级别进行的实验检索了病变图像的相关图像和类似图像平均平均精度为0.85。呈现的系统是预期的助剂，提高诊断的E态由放射科医生进行。

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《SPIE Medical Imaging Conference》|2019年|1 CD-ROM|共6页
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Swarnambiga Ayyachamy; Ganapathy Krishnamurthi;
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中图分类计算技术、计算机技术;
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Case Based Image Retrieval and Clinical Analysis of Tumor and Cyst

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