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Case Based Image Retrieval and Clinical Analysis of Tumor and Cyst

机译:基于病例的图像检索及肿瘤和囊肿的临床分析

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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 eectiveness of diagnosisperformed by radiologist.
机译:具有图像检索功能的基于案例的推理(CBR)可用于实施临床决策支持系统 支持诊断占位性病变。我们提出了一个基于案例的图像检索(CBIR)系统,以 检索病变与输入测试图像相似的图像。在这里,我们仅考虑脑胶质瘤和肺癌 病变。肺癌病变可以是结节或囊肿。特征数据库已创建,并且 查询的处理是实时进行的。通过使用视觉单词袋(BOVW),特征直方图为 与密码本进行比较以检索相似的图像。 在各个级别进行的实验使用 平均平均精度为0.85。提出的系统可望为您带来帮助,并提高诊断的有效性 由放射科医生进行。

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