physics

Region of interest

Region of interest is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Region of interest rather than just read about it. In short: A region of interest (often abbreviated ROI) is a sample within a data set identified for a particular purpose. The concept of a ROI is commonly used in many application areas.

Key takeaways

Region of interest belongs to physics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Region of interest to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Region of interest from memory before moving on to harder problems.

Reference excerpt

A region of interest (often abbreviated ROI) is a sample within a data set identified for a particular purpose. The concept of a ROI is commonly used in many application areas. Existing as a vicinity, or within one. 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 1D dataset: a time or frequency interval on a waveform 2D dataset: the boundaries of an object on an image 3D dataset: the contours or surfaces outlining an object (sometimes known as the Volume of Interest (VOI)) in a volume 4D dataset: the outline of an object at or during a particular time interval in a time-volume 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 a structured form. There are three fundamentally different means of encoding a ROI:

As an integral part of the sample data set, with a unique or masking value that may or may not be outside the normal range of normally occurring values and which tags individual data cells As separate, purely graphic information, such as with vector or bitmap (rasterized) drawing elements, perhaps with some accompanying plain (unstructured) text in the format of the data itself As a separate structured semantic information (such as coded value types) with a set of spatial and/or temporal coordinates

Medical imaging

Medical imaging standards such as DICOM provide general and application-specific mechanisms to support various use-cases. For DICOM images (two or more dimensions):

Burned in graphics and text may occur within the normal pixel value range (e.g., as the maximum white value) (deprecated) Bitmap (rasterized) overlay graphics and text may be present in unused high bits of the pixel data or in a separate attribute (deprecated) Vector graphics may be encoded in separate image attributes as curves (deprecated) Unstructured vector graphics and text as well as bitmap (rasterized) overlay graphics may be encoded in a separate object as a presentation state that references the image object to which it is to be applied Structured data may be encoded in a separate object as a structured report in the form of a tree of name-value pairs of coded or text concepts possibly associated with derived quantitative information can reference spatial and/or temporal coordinates that in turn reference the image objects to which they apply Reference locations may be encoded as fiducials in the form of spatial coordinates with an associated coded purpose, either as pixel coordinates by reference to specific images or as coordinates in a named patient-relative 3D Cartesian space Pixels (possibly non-contiguous) may be classified into segments encoded in a segmentation object as either binary or probabilistic values in a raster (which is not required to have the same spatial sampling or extent as the images from which the segmentation was derived); these are usually referenced by other objects containing structured content (structured reports) For DICOM radiotherapy:

Contours of objects may be defined as structure sets, either as pixel coordinates by reference to specific images or as coordinates in a named patient-relative 3D Cartesian space (these are also used for non-RT applications) For DICOM time-based waveforms:

Burned in values may occur with the waveform (deprecated) Annotations may be encoded in a separate attribute can select multiple time points or a range of time points, either by sample number or specified time Structured data may be encoded in a separate object as a structured report in the form of a tree of name-value pairs of coded or text concepts possibly associated with derived quantitative information can reference temporal coordinates that in turn reference the waveform objects to which they apply 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

Illustrations

Worked examples

Example 1 — a first encounter with Region of interest

Start with the simplest possible case. Write down what Region of interest claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Region of interest before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Region of interest ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Region of interest

In research: Region of interest appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Region of interest in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Region of interest is common in secondary-school and first-year university syllabi. It links to neighbouring topics Geographic information systems, Medical imaging, Optical character recognition, so understanding it makes those chapters shorter.
In everyday life: Look for Region of interest outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Region of interest in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Region of interest means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Region of interest out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Region of interest in simple terms?

A region of interest (often abbreviated ROI) is a sample within a data set identified for a particular purpose. The concept of a ROI is commonly used in many application areas.

Why does Region of interest matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Region of interest?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Region of interest.