基于LSTM网络的医学图像有损压缩

G. N. Prabhu, Trisiladevi C. Nagavi, P. Mahesha
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引用次数: 1

摘要

与普通图像相比,医学图像具有更大的尺寸。在大量医学图像的存储和传输中出现了一个问题。因此,有必要压缩这些图像,以尽可能地减小大小,并保持更好的质量。提出了一种基于递归神经网络(RNN)的医学图像有损压缩方法。因此,该方法产生可变压缩率的图像,以保持图像的质量,并保留图像中存在的一些重要内容。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical Image Lossy Compression With LSTM Networks
Medical images have a larger size when compared to normal images. There arises a problem in the storage as well as in the transmission of a large number of medical images. Hence, there exists a need for compressing these images to reduce the size as much as possible and also to maintain a better quality. The authors propose a method for lossy image compression of a set of medical images which is based on Recurrent Neural Network (RNN). So, the proposed method produces images of variable compression rates to maintain the quality aspect and to preserve some of the important contents present in these images.
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