Types of Image Compression for Medical Imaging Essay

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Medical imaging, as we all know, is the process of taking images of various parts of the human body for diagnostic and surgical purposes. Some of the popular medical imaging modalities are X-ray radiography, Magnetic resonance imaging, Medical ultrasound, Computed tomography etc. Since, these images contain clinical data of extreme importance for treatment follow-ups and are acquired at cost of radiation exposure, infrastructure, money and time involved. Thus, once acquired, the medical imaging data should not be disposed off casually, instead it should be retained so that it can be utilized for various medical applications and the chances of repeated testing can be minimized. Also, maintaining electronic health records of patients serves …show more content…

In other words an optimal compression ratio should be chosen so as to suit the needs of medical examination, without compromising with its diagnostic value [2].
1.2 Types of Compression
Image compression can be classified into two types viz. lossless and lossy compression.

Lossless compression is the technique of reducing the size of an image without any virtual loss of information. It is also known as reversible form of image compression since the image obtained after compression and then decompression resembles the original one. Typical compression ratios that can be achieved ranges from 1.5 to 3.6 [3].
Conversely, lossy or irreversible form of compression techniques are those in which some or the other information is always lost. Though, lossy compression algorithms are capable of compressing images at ratios much higher than that achieved from lossless compression thus, ensuring faster rates of transmission and lesser storage space. However, the regenerated image is not guaranteed to be an exact replica of the original image, as some data is lost permanently, which will cause error during decompression. Typical compression ratios achieved may range from 5 to 50.
Though lossy data compression is often acceptable but the game is not that easy when it comes to medical images. The data from medical imaging examination should possess certain requirements for fidelity [3].
1.3 Barriers to image compression
Lossy compression:

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