Experimental results for medical image show that the presented method can efficiently code multiple ROIs based on different degrees of interest without any shape information of the ROIs.
Abstract: Region of Interest (ROI) coding technique is significant for medical image compression and transmission.
So a new image compression scheme called region of interest (ROI) coding was presented in [1]-[7].
The basic idea of ROI coding is that certain parts of the image that are of higher importance than others are encoded at higher quality than the background (BG) and are transmitted first or at a higher priority [1]-[5].
The Maxshift method exploits the possibility of representing an arbitrarily shaped ROI by shifting the ROI coefficient values on the top of the BG coefficient range.
In this paper, we presented a new and efficient ROI coding method for medical image based on bitplane shift scheme, which is called general layered bitplane shift (GLBShift) method.
In Section 2, the several main ROI coding methods for the medical image are reviewed.
ROI image coding is a new feature in JPGE2000, which allows ROI to be coded with better quality than the rest of an image.
Another classic use of the ROI calculation is to justify the improvement of information management through technology.
It is highly unlikely in this case that an ROI calculation will ever provide an ROI of greater than 1.
By recognizing all the financial outcomes from the system, the ROI calculation can exceed 1 by several factors.
In both cases, the classic ROI calculation provides guidance on the value of the investment.
Another way to look at ROI is from the risk of inaction perspective.
No realistic ROI formula, in the classic sense, can be devised to calculate the cost of inaction.
Another ROI that has become increasingly important is the risk of incarceration.
