Computational 2D and 3D Medical Image Data Compression Models

In this world of big data, the development and exploitation of medical technology is vastly increasing and especially in big biomedical imaging modalities available across medicine. At the same instant, acquisition, processing, storing and transmission of such huge medical data requires efficient and robust data compression models. Over the last 2 decades, numerous compression mechanisms, techniques and algorithms were proposed by many researchers. This work provides a detailed status of these existing computational compression methods for medical imaging data. Appropriate classification, performance metrics, practical issues and challenges in enhancing the two dimensional (2D) and three dimensional (3D) medical image compression arena are reviewed in detail.

Automated summary

With the rapid development and utilization of medical technology in the era of big data, efficient and robust data compression models are required to handle the huge amount of medical imaging data. Researchers have proposed numerous compression mechanisms and algorithms in the past two decades to address this challenge, with this work providing a detailed overview of existing computational compression methods in the field of medical imaging data.