利用皮肤镜兴趣点检测定位和检索皮肤镜图像中色素网络的CBIR系统

Ardalan Benam, M. S. Drew, M. S. Atkins
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引用次数: 7

摘要

我们设计了一个基于内容的皮肤镜图像检索(CBIR)系统,重点关注具有色素网络的图像。该系统将具有色素网络的查询图像与皮肤镜图像数据库中包含色素网络的最相似的图像进行定位和匹配。检测查询图像中的皮肤镜兴趣点,并从每个关键点提取128个特征向量作为描述符。然后,根据我们的匹配算法将描述符与数据库图像中出现的相似特征进行匹配。这导致了有意义的匹配,因为我们正在将相似的皮肤镜结构相互匹配。该系统的性能已在1000多张图像上进行了测试。结果表明,该系统能够利用色素网络对相似图像进行定位和检索,准确率达75.4%。该系统可以帮助医生进行诊断,因为他们可以看到与已知病理相似的皮肤镜图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A CBIR system for locating and retrieving pigment network in dermoscopy images using dermoscopy interest point detection
We designed a content based image retrieval (CBIR) system for dermoscopic images focusing on images with pigment networks. The system locates and matches a query image that has a pigment network with the most similar images containing pigment networks in a database of dermoscopic images. Dermoscopy interest points in the query image are detected and a vector of 128 features is extracted as the descriptor from each keypoint. Then, the descriptors are matched according to our matching algorithm to similar features arising in the database images. This leads to a meaningful matching as we are matching similar dermoscopy structures with each other. The performance of the system has been tested on more than 1000 images. Results show that our system will locate and retrieve similar images with pigment networks, with accuracy > 75.4%. This system can help physicians in diagnosis as they are shown similar looking dermoscopy images with known pathology.
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