Medical Image Lossy Compression With LSTM Networks

View Sample PDF

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: 2023
Pages: 18
Source title: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-7544-7.ch027

Keywords: Knowledge Management and Library Science / Medical Diagnosis and Practice / Medical Imaging / Medical Information Science Reference

Purchase

View Medical Image Lossy Compression With LSTM Networks on the publisher's website for pricing and purchasing information.

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.

The IRMA Community

Research IRM

Medical Image Lossy Compression With LSTM Networks

Purchase

Abstract

Related Content

IRMA Sponsors