Computational 2D and 3D Medical Image Data Compression Models
| Autor: | V. B. Surya Prasath, P. Kalavathi, V. Punitha, S. Boopathiraja |
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| Rok vydání: | 2021 |
| Předmět: |
Modalities
Computer science business.industry Applied Mathematics Big data Robust statistics Health technology 02 engineering and technology computer.software_genre 01 natural sciences Article Computer Science Applications 010101 applied mathematics Compression (functional analysis) 0202 electrical engineering electronic engineering information engineering Medical imaging 020201 artificial intelligence & image processing Data mining 0101 mathematics business computer Data compression Image compression |
| Zdroj: | Arch Comput Methods Eng |
| ISSN: | 1886-1784 1134-3060 |
| Popis: | 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 two 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. |
| Databáze: | OpenAIRE |
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