Medical Image Storage Calculator

Calculate the storage requirements for medical imaging studies.

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Study Size
Size in GB0.1

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Assumptions

  • The estimate is based on uncompressed pixel data plus a simple metadata overhead percentage.
  • Real archive usage varies with transfer syntax, compression, multi-series packaging, replicas, and lifecycle policies.
  • This calculator is for capacity planning and should not be treated as an exact PACS billing or storage-accounting figure.

Sensitivity preview

Matrix Rows (Y) -10%: Study Size 91.8 MB

Matrix Rows (Y) Current: Study Size 102 MB

Matrix Rows (Y) +10%: Study Size 112.2 MB

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About this DICOM Storage Estimator

Medical imaging generates massive amounts of data. PACS administrators and IT professionals use this calculator to plan storage arrays by estimating the size of uncompressed DICOM studies based on resolution and slice count.

Who this calculator is for

  • PACS administrators, imaging IT teams, and engineers sizing storage for imaging archives.
  • People estimating the footprint of CT, MR, mammo, or multi-frame studies before compression.
  • Learners studying how matrix size, bit depth, and frame count drive archive growth.

When to use it

  • Use this tool when comparing storage impact across modalities or protocol variants.
  • Use it to produce a fast back-of-the-envelope estimate before PACS, VNA, or cloud planning.
  • Use it when teaching the difference between raw pixel payload and full operational storage needs.

How to use this calculator

  1. Enter the matrix Rows and Columns (e.g., 512x512 for CT).
  2. Enter the Number of Images in the study.
  3. Select the Bit Depth (usually 16-bit for radiology).
  4. Add a percentage for Header Overhead (metadata).

Key assumptions

  • The estimate is based on uncompressed pixel data plus a simple metadata overhead percentage.
  • Real archive usage varies with transfer syntax, compression, multi-series packaging, replicas, and lifecycle policies.
  • This calculator is for capacity planning and should not be treated as an exact PACS billing or storage-accounting figure.

Accuracy and testing

Review formula sources, default test cases, assumptions, unit handling, rounding rules, and changelog for this calculator.

View accuracy page

How this calculator works

Total Bits = Rows × Columns × Bit Depth × Images Total Bytes = Total Bits / 8 The result is converted to MB or GB. Note that this calculates *uncompressed* size. Lossless compression (like JPEG-LS) can reduce this by 2-3x.

Inputs explained

Matrix

Dimensions of the image. CT/MR is usually 512x512. CR/DR can be 2000x2000 or higher. Mammography can be 4000x4000.

Bit Depth

Most radiology images are 12-bit or 16-bit (Allocated). Ultrasound/Nuclear are often 8-bit (Color/Grayscale).

Overhead

DICOM headers contain patient info. Usually adds 1-2% to the file size.

Understanding your results

A 1000-slice CT scan is roughly 500MB uncompressed. A 4-view Mammogram can be 160MB-200MB.

Example scenarios

Standard CT

512x512, 16-bit, 200 slices. Size: ~100 MB.

Digital Mammo (Tomosynthesis)

2500x3000, 16-bit, 300 slices. Size: ~4.2 GB.

Key Features

  • Supports standard matrices (512, 1024, 2048)
  • Calculates uncompressed size
  • Include DICOM header overhead

Frequently Asked Questions

What is the typical file size of a CT scan?
A standard chest CT might have 200-500 slices at 512x512 resolution (16-bit). This results in a study size roughly between 100MB and 300MB.
Does this account for compression?
No, this calculator estimates the raw, uncompressed data size. Most PACS use lossless compression (like JPEG-LS) which can reduce storage needs by 2:1 or 3:1.
Why is 16-bit depth common?
Most modern modalities (CT, MRI, CR) capture data in 10-12 or 16 bits to preserve the full dynamic range of grayscale values (Hounsfield units, signal intensity), unlike standard consumer images which are 8-bit.