.png){kind=icon}
.png){kind=icon}
Return
Computational 2D and 3D Medical Image Data Compression Models
.png){kind=icon}
OA
AI
DOI：10.1007/s11831-021-09602-w.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
LOSSLESS COMPRESSION
DICOM IMAGES
EFFICIENT
DECOMPOSITION
TRUNCATION
TRANSFORM
VIDEO
INFORMATION
REGION
VOLUME
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
12.1
Papers:
1.8K
Citations:
1.2W