Region of interest

In computer vision and optical character recognition, the ROI defines the borders of an object under consideration.

In many applications, symbolic (textual) labels are added to a ROI, to describe its content in a compact manner.

There are three fundamentally different means of encoding a ROI: Medical imaging standards such as DICOM provide general and application-specific mechanisms to support various use-cases.

In Optical Character Recognition (OCR) and Document Layout Analysis, regions of interest (ROIs) hierarchically encompass pages, text or graphical blocks, down to individual line-strip images, word and character image boxes.

As far as non-medical standards are concerned, in addition to the purely graphic markup languages (such as PostScript or PDF) and vector graphic (such as SVG) and 3D (such as VRML) drawing file formats that are widely available, and which carry no specific ROI semantics, some standards such as JPEG 2000 specifically provide mechanisms to label and/or compress to a different degree of fidelity, what they refer to as regions of interest.

The region of interest for which Markov's inequality gives a lower bound.
The left image shows an original mammogram before MED-SEG processing. The image on the right, with region of interest (white) labeled, shows a mammogram after MED-SEG processing.