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Extraction of Abnormalities in MRI, CT, X-ray and Ultrasound Images Towards Development of Efficient Compression Algorithm

机译:提取MRI,CT,X射线和超声图像中的异常,以开发高效压缩算法

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摘要

Compression of medical images is essential for teleradiology applications. Medical image compression saves time and bandwidth during data transmission and also reduces storage space. For medical images, the diagnostically useful information termed Region of Interest (ROI) is localized in a small area. A compression algorithm to preserve high quality in diagnostically significant regions and allowing degradation in other regions providing higher compression is necessary. In this proposed work, ROI is processed using lossless compression algorithm and lossy compression elsewhere in the image. Variational level sets with distance regularization segment ROI. The compression algorithm is developed to obtain image with high optimum compression efficiency and also with high fidelity, especially for ROI. A new threshold based medical image compression with edge preservation is proposed to preserve diagnostic information within ROI. The performance of the proposed ROI based compression algorithm is compared in terms of Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR).
机译:医学图像的压缩对于远程放射学应用至关重要。医学图像压缩节省了数据传输期间的时间和带宽,还减少了存储空间。对于医学图像,称为有用区域(ROI)的诊断有用信息位于一个小区域中。需要一种压缩算法以在诊断上重要的区域中保持高质量,并允许其他区域中的退化以提供更高的压缩率。在这项拟议的工作中,使用无损压缩算法和图像中其他位置的有损压缩来处理ROI。具有距离正则化分段ROI的变化水平集。开发压缩算法以获得具有最佳压缩效率和高保真度的图像,尤其是对于ROI。提出了一种新的基于阈值的具有边缘保留的医学图像压缩方法,以在ROI中保留诊断信息。根据压缩比(CR)和峰值信噪比(PSNR)比较了所提出的基于ROI的压缩算法的性能。

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