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The improvement for extraction technology to target tissue of medical image

机译:提取技术的改进对医学形象组织的提取技术

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The current extracting approach to the target tissue of medical image has the problem of extracting speed. This paper presented a method of extracting the interesting area rapidly from the medical image file. Firstly, by combining run-length coding with block coding, the new coding could extract the medical image data rapidly, which not only saved the memory space and improved transmission efficiency, but also could read the required single pixel, or part of pixel data from the compressed data conveniently. Next, the author realized the extraction of interesting tissue based on combining threshold segmentation with seeded region growing, which could save the memory space and realize image segmentation rapidly and stably. Finally, The improvement mentioned above has been realized in 3D reconstructing software-MedLG which was developed by authors' institute and applied successfully in customized prostheses designing.
机译:医学图像的目标组织的当前提取方法具有提取速度的问题。本文提出了一种从医学图像文件中快速提取有趣区域的方法。首先,通过将运行长度编码与块编码组合,新编码可以快速提取医学图像数据,这不仅保存了存储空间和提高的传输效率,还可以读取所需的单像素或来自的一部分像素数据压缩数据方便。接下来,作者意识到基于与种子区域生长的组合阈值分割的有趣组织的提取,这可以节省存储空间并快速且稳定地实现图像分割。最后,上面提到的改进已经实现在3D重建软件-Medlg中,由作者研究所开发,并在定制的假体设计中成功应用。

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