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Medical Image Lossy Compression With LSTM Networks
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Author(s): Nithin Prabhu G. (JSS Science and Technology University, India), Trisiladevi C. Nagavi (JSS Science and Technology University, India) and Mahesha P. (JSS Science and Technology University, India)
Copyright: 2019
Pages: 22
Source title:
Histopathological Image Analysis in Medical Decision Making
Source Author(s)/Editor(s): Nilanjan Dey (Techno India College of Technology, India), Amira S. Ashour (Tanta University, Egypt), Harihar Kalia (Seemantha Engineering College, India), R.T. Goswami (Techno India College of Technology, India) and Himansu Das (KIIT University, India)
DOI: 10.4018/978-1-5225-6316-7.ch003
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Abstract
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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