Region of interest

The region of interest for which Markov's inequality gives a lower bound.

A region of interest (often abbreviated ROI), is a selected subset of samples within a dataset identified for a particular purpose.[1] The concept of a ROI is commonly used in many application areas. For example, in medical imaging, the boundaries of a tumor may be defined on an image or in a volume, for the purpose of measuring its size. The endocardial border may be defined on an image, perhaps during different phases of the cardiac cycle, for example end-systole and end-diastole, for the purpose of assessing cardiac function. In geographical information systems (GIS), a ROI can be taken literally as a polygonal selection from a 2D map. 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. Within a ROI may lie individual points of interest (POIs).

Examples of regions of interest

A ROI is a form of annotation, often associated with categorical or quantitative information (e.g., measurements like volume or mean intensity), expressed as text or in structured form.

There are three fundamentally different means of encoding a ROI:

Medical imaging

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.

Medical imaging standards such as DICOM provide general and application-specific mechanisms to support various use-cases.

For DICOM images (two or more dimensions):

For DICOM radiotherapy:

For DICOM time-based waveforms:

HL7 Clinical Document Architecture also has a subset of mechanisms similar to (and intended to be compatible with) DICOM for referencing image-related spatial coordinates as observations; it allows for a circle, ellipse, polyline or point to be defined as integer pixel-relative coordinates referencing an external multi-media image object, which may be of a consumer rather than medical image format (e.g., a GIF, PNG or JPEG).

Document analysis systems

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. The de facto standard in archives and libraries is the tuplet {image_file,xml_file}, usually in the form of a *.tif file and its accompanying *.xml file.

Other 2D applications

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.

References

  1. Ron Brinkmann (1999). The Art and Science of Digital Compositing. Morgan Kaufmann. p. 184. ISBN 978-0-12-133960-9.
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