Pixel operations

Crop / ROI extraction

Crop pixel data to a region of interest and export the trimmed image.

Problem

You have a DICOM image with a large field of view (e.g. 512×512 whole-abdomen CT) but only need a specific region — a 100×100 pixel ROI around the liver for a focused analysis or AI model input. Cropping reduces file size, focuses analysis on the region of interest, and removes extraneous anatomy.

Steps

Open the file (⌘O) and record the original Image Position (Patient) (0020,0032) and Rows/Columns (0028,0010/0011) in Edit mode.
Open Pixel Operations — ⌘K → “Pixel operations…” or access from the top bar.
Select Crop from the pixel operation picker.
Enter ROI coordinates:
- X (left): 20
- Y (top): 20
- Width: 100
- Height: 100
Click Apply transform — the cropped image is derived and staged in memory.
Verify — filter for Rows (0028,0010) and Columns (0028,0011). Both should be 100. The Image Position (Patient) (0020,0032) is shifted to reflect the new spatial origin.

Validation

Width and Height inputs enforce a minimum of 1. Entering 0 snaps back to 1 (zero-area crop is structurally impossible).
The default crop dimensions are the full image dimensions (non-zero, pre-filled).

Result

The output is a 100×100 derived copy with Image Position (Patient) shifted for the crop offset and a regenerated 2.25.* SOP Instance UID; the original is unchanged, and zero-area crops are clamped to a 1-pixel minimum.