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Application of Fisher Score and mRMR Techniques for Feature Selection in Compressed Medical Images

机译:Fisher评分和mRMR技术在压缩医学图像特征选择中的应用

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In nowadays there is a large increase in the digital medical images and different medical imaging equipments are available for diagnoses, medical professionals are increasingly relying on computer aided techniques for both indexing these images and retrieving similar images from large repositories. To develop systems which are computationally less intensive without compromising on the accuracy from the high dimensional feature space is always challenging. In this paper an investigation is made on the retrieval of compressed medical images. Images are compressed using the visually lossless compression technique. Shape and texture features are extracted and best features are selected using the fisher technique and mRMR. Using these selected features RNN with BPTT was utilized for classification of the compressed images.
机译:如今,数字医学图像已大大增加,并且可以使用不同的医学成像设备进行诊断,医学专业人员越来越依赖计算机辅助技术来对这些图像进行索引并从大型存储库中检索相似的图像。开发在计算上不那么费力的系统而又不影响高维特征空间的精度始终是一个挑战。本文对压缩医学图像的检索进行了研究。使用视觉无损压缩技术压缩图像。使用费舍尔技术和mRMR提取形状和纹理特征并选择最佳特征。使用这些选定的特征,将带有BPTT的RNN用于压缩图像的分类。

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