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435 pts.
 Imaging Data Capacity Analysis
The images are high volume data.How the storage needs are assessed while planning for PACS.what are the baseline used for calculation of image and study size for the different imaging modalities.what are the other factors needs to be taken into account.

ASKED: June 10, 2010  10:52 AM
UPDATED: January 5, 2011  12:59 pm

Answer Wiki:
Typically, your modality and/or PACS vendors should be able to give you an estimated size per study. Also, it is important to know if these studies will be stored compressed or uncompressed. For example, a typical CT study may consume 80MB uncompressed or 15MB compressed, whereas a typical MR study may consume 40MB uncompressed or 8MB compressed. Once you have this data, you then need to project the number of studies per year over the n number of years you expect to get out of the storage. You should also consider a storage tiering strategy and how your medical image storage fits into your enterprise storage strategy.
Last Wiki Answer Submitted:  June 11, 2010  7:57 pm  by  Cmallio   15 pts.
All Answer Wiki Contributors:  Cmallio   15 pts.
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Yes, your vendor should be able to get you that estimate, based upon the vendor DICOM size of your images. For Archives here is a simple formula for calulating as you requested:

1) Determine the average number of images per exam within your office (A)
2) Have the vendor give you the DICOM size of the image in Bytes (B)
3) Multiply A & B for an Average Exam Size (AES) (C)
4) Take the AES and multiply it by the volume of your modalities (CT, MRI), which tells you your annual volume needs (D)
5) Multiply D times the number of years you need to archive (7).

This should get you close!

 390 pts.

 

The process of supplying image data to end users is not a new concept. The demand for this service has grown. As a result of this increase in demand, the method for storing and retrieving images has caused IT services all around to rethink, re-engineer, and re-architect installations supporting this technology. Currently we are monitoring all the processes supporting these image request transactions for performance, scalability and adverse event. We are developing criteria for a statistical model to feed an On-Line Analytical Processing (OLAP) engine to provide an automated enterprise management system (EMS) solution. More details to come.

 280 pts.

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