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首页> 外文期刊>Research Journal of Fisheries and Hydrobiology >MRI brain image enhancement using transfer learning and quaternion matrix analysis
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MRI brain image enhancement using transfer learning and quaternion matrix analysis

机译:使用转移学习和四元数矩阵分析的MRI脑图像增强

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MRI brain image enhancement is a complex task in the biomedical imaging field but very useful for classification of the brain tissue. Theautomatic segmentation of brain-tissue has led to the variation in the images due to different scanning and the imaging protocols whichmakes the image unclear and thus application is hampered. The transfer learning with weighted SVM enables training data to minimizeclassification errors as the classification scheme needs only a small amount of representative data. Therefore a new optimally standardizedmethod is presented for scanned image segmentation using Transfer Learning with Weighted Support Vector Machine and then furtherimproving the training data quality by Vector Sparse Representation using Iterative Algorithm for Quaternion Matrix Analysis overReflexive Matrices.
机译:MRI脑图像增强是生物医学成像领域中的一项复杂任务,但对脑组织的分类非常有用。由于不同的扫描和成像方案,脑组织的自动分割导致图像的变化,这使图像不清楚,因此妨碍了应用。加权SVM的转移学习使训练数据能够最大程度地减少分类错误,因为分类方案仅需要少量代表性数据。因此,提出了一种新的最优标准化方法,该方法用于使用加权支持向量机的转移学习进行扫描图像分割,然后使用自反矩阵四元数矩阵分析的迭代算法通过向量稀疏表示进一步提高训练数据质量。

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