mitkImageStatisticsHotspotTest

Testcases

To check the correctness of the hotspot calculation, this special class has been created, which generates images with known hotspot location and statistics. A number of unit tests use this class to first generate an image of known properties and then verify that mitk::ImageStatisticsCalculator is able to reproduce the known statistics.

Every testcase has a defined hotspot, maximum and minimum including their corresponding index-values and mean value. The XML-files to each testcase is located in Modules/ImageStatistics/Testing/Data.

This test checks the hotspot-statistics of images with a spacing[x,y,z] of [3,3,3], [4,4,3] and [5,5,5], according to common PET-resolutions.

The following cases describe situations of hotspot-calculation and their supposed results.

Note: Below only the behaviour of maximum is mentioned mostly, but the other statistics (minimum and mean) behave in the same way like maximum.

Testcase 1: No values outside of hotspot are used for statistic-calculation

The purpose of this testcase is primarily to confirm the correct detection of the hotspot even if there is an global maximum which is "hotter" than the mean value itself. On the other hand the test verifies that only voxels are used for statistic-calculation which are located in the hotspot.

Description:

• Defined location of hotspot in image: left upper corner
• Defined location of maximum in image: bottom right corner
• Segmentation is not available

Assumed results:

• Hotspot is calculated correctly in the left upper corner of the image
• Defined maximum is not inside hotspot
• A maximum inside the hotspot is calculated

Testcase 2: Correct detection of hotspot

In this testcase we want to make sure that when a segmentation is available the origin of the hotspot-sphere is located within it. The image is so structured that there are two hot regions: One region inside and another one, which is hotter than the other region, outside the segmentation. So we can assume that the segmentation is also considered when detecting the hotspot, even an actual hotspot outside the segmentation exists.

Description:

• Segmentation is available
• Defined location of hotspot: inside segmentation
• Defined location of maximum: inside hotspot
• Another "hotter" region outside of the segmentation

Assumed results:

• Defined hotspot is correctly calculated inside segmentation
• Defined maximum is correctly calculated inside hotspot
• "Hotter" region outside of segmentation is disregarded

Testcase 3: Correct calculation of statistics in hotspot, although the whole hotspot is not inside segmentation

The difficulty of calculating the hotspot statistics in testcase 3 is that the origin of the hotspot is close to the segmentation-borders. So if the whole hotspot is not inside the segmentation (or even the segmentation is smaller than the hotspot itself) this test checks that calculation of hotspot statistics is possible anyway.

Description:

• Segmentation is available
• Defined location of hotspot: inside segmentation
• Defined location of maximum: outside of segmentation, but inside of hotspot

Assumed results:

• Defined hotspot is correctly calculated inside segmentation
• Defined maximum is correctly calculated inside hotspot although it is located outside of the segmentation

Testcase 4 and 5: Hotspot must (not) be completely inside image

Testcase 4 and 5 are very similar so we mention it at the same time: In testcase 4 the hotspot is not completely inside the image and just voxels are considered for calculation which are located inside the image. But in testcase 5 the hotspot must be completely inside the image even there is an possible hotspot-location at the borders of the image.

Description:

• Defined location of hotspot: At the border of the image
• Defined location of maximum: Inside hotspot
• Segmentation is not available

Assumed results in testcase 4:

• Just the part of the hotspot, which is located in the image, is used for statistics-calculation
• Defined statistics are calculated correctly

Assumed results in testcase 5:

• Defined hotspot and statistics are not calculated, because hotspot is not completely inside image
• A hotspot, which is not as hot as the defined one but is inside the image, is calculated

Testcase 6: Multi label mask

This testcase confirms that mitkImageStatisticsCalculator has the possibility to calculate hotspot statistics even if there are multiple regions of interest.

Description:

• Two defined regions of interest with defined statistics for each one.

Assumed results:

• In every region of interest there are correctly calculated hotspot-statistics