DICOM PS3.3 2018a - Information Object Definitions

C.11.5 Image Histogram Module
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### C.11.5 Image Histogram Module

Table C.11.5-1. Image Histogram Module Attributes

Attribute name | Tag | Type | Description
--- | --- | --- | ---
Histogram Sequence | (0060,3000) | 1 | Defines a sequence of Histograms. One or more Items shall be included in this Sequence.
>Histogram Number of Bins | (0060,3002) | 1 | The number of "bins" (entries) in the histogram.
>Histogram First Bin Value | (0060,3004) | 1 | The stored pixel value corresponding to the lowest pixel value counted in the first bin. All image pixel values less than this value are not included in the histogram. ### Note The Value Representation of this Attribute is determined by the value of Pixel Representation (0028,0103).
>Histogram Last Bin Value | (0060,3006) | 1 | The stored pixel value corresponding to the highest pixel value counted in the last bin. All image pixel values greater than this value are not included in the histogram. ### Note The Value Representation of this Attribute is determined by the value of Pixel Representation (0028,0103).
>Histogram Bin Width | (0060,3008) | 1 | The number of consecutive stored pixel values included in a bin. All bins shall be of equal width.
>Histogram Explanation | (0060,3010) | 3 | Free form text explanation of the meaning of the LUT.
>Histogram Data | (0060,3020) | 1 | Histogram Data encoded as 32 bit unsigned counts of the number of pixel values in each bin.

#### C.11.5.1 Image Histogram Attribute Descriptions

The Image Histogram is a multi-valued sequence representing a sequential count of binned stored image pixel values in ascending order.

### Note

One reason to include a histogram with an image is as an aid to image processing applications. For applications that use them, computations of histograms for very large images can be a significant burden on computer resources and can seriously degrade the response time to the user.

The Image Histogram is multi-valued to support multiple histograms per image. One or more regions of interest or value ranges may be separately computed. A description of the region(s) of interest and value range may be included in Histogram Explanation (0060,3010). The Image Histogram may be related to parts or all of a specific image.

The Attributes describing the parameters of the histogram are in image pixel value space, as stored in Pixel Data (7FE0,0010), before the application of any transformation such as Rescale Slope and Intercept or Modality LUT.

The range of stored image pixel value instances is described by the Histogram First Bin Value (0060,3004) and Histogram Last Bin Value (0060,3006). All values outside of this range shall be ignored. The number of histogram bins shall be large enough to contain all of the pixels in the range from the smallest to the largest stored image pixel value in that region of the image from which the histogram has been derived (which may or may not be the whole image).

The Histogram Bin Width (0060,3008) describes how many consecutive stored image pixel values are counted as one. All bins shall be of equal width.

### Note

For example, a Histogram Bin Width (0060,3008) of 8 means that counts of pixel values in ascending groups of 8 are added together. If Histogram First Bin Value (0060,3004) were 0, then the first bin would contain the count of pixel values in the range of 0-7, the second bin the count of pixel values in the range of 8-15, etc. If Histogram Number of Bins (0060,3002) were 32, then the last bin would contain the count of pixel values in the range of 248-255 and Histogram Last Bin Value (0060,3006) would be 255 (not 248).

This example is illustrated in Figure C.11.5-1, in which the vertical axis represents the count within each bin and the horizontal axis represents each bin in ascending order.

Figure C.11.5-1. Image Histogram Example

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DICOM PS3.3 2018a - Information Object Definitions