Hi!
I downloaded the mouse brain data sets (annotation_x.nrrd) from the download server. While analysing these data sets in ImageJ I noticed that the labeled sections are not always connected. For many labels single voxels are present. Is this correct or might I be doing something wrong?
And could someone please tell me where I can get a table with a description of the corresponding brain sections?
many thanks in advance!
Best regards, Mark
Hi Mark,
I wasn’t able to recreate the issue you’re having myself, but I did find that loading the annotation files directly into ImageJ can appear odd given the large difference in structure ID values. There is a modified 25 micron annotation file that keeps the structure IDs within a smaller range of values, and it comes associated with a labels text file that links those structure IDs to structure acronyms. You can find the CCFv3_annotation_25.nrrd and associated CCFv3_annotation_OntologyColor_labels.txt file here and see if you still have the same problem.
Also, if that doesn’t solve your problem, please share the coordinates of some of these unconnected voxels and I’ll take a closer look.
Maitham
Hi Maitham,
Thanks a lot for your response.
I downloaded the data set (and the corresponding OntologyColor_labels) and performed the same procedure. Unfortunately, as a result I get again lots of small objects.
In ImageJ I imported the data set as *.nrrd and segmented the voxel with ID = 24. As a result, I get one large object and a single voxel object:
After saving the data as *.tiff I loaded the data into Arivis and performed a labeling on the full data set. For label = 24 I also get these two objects:
Name Max, Intensities #1 Volume, Volume (µm³) Center Z, 3D Oriented Bounds (µm) Center X, 3D Oriented Bounds (µm) Center Y, 3D Oriented Bounds (µm)
Segment #569 (Labeled Image Segmenter) 24 1 278.5 68 159
Segment #3643 (Labeled Image Segmenter) 24 48643 227.9839172 139.6567383 200.2678375
As an attachment I sent you the full list of objects I got from the Arivis analysis. As you can see there are many single voxel objects.
It would be great if you could have a closer look and could identify why these small objects occur.
Best regards,
Mark
(Attachment CCFv3_annotation_25-features.csv is missing)
Hi Maitham,
Since I couldn’t send you the *.csv as an attachment, here another example with many small and two larger objects.
Best regards, Mark
[ID=47]:
Segment #003 (Labeled Image Segmenter) 47 1 79.5 249 196
Segment #032 (Labeled Image Segmenter) 47 86 92.33495331 204.8926392 199.0583038
Segment #036 (Labeled Image Segmenter) 47 1 91.5 211 203
Segment #041 (Labeled Image Segmenter) 47 1 80.5 234 192
Segment #042 (Labeled Image Segmenter) 47 1 80.5 236 193
Segment #092 (Labeled Image Segmenter) 47 1 81.5 232 193
Segment #093 (Labeled Image Segmenter) 47 5 81.66876221 234.2218781 195.5594025
Segment #129 (Labeled Image Segmenter) 47 1 82.5 228 192
Segment #179 (Labeled Image Segmenter) 47 1 83.5 226 193
Segment #253 (Labeled Image Segmenter) 47 9 85.57202148 218.0462494 193.4315033
Segment #300 (Labeled Image Segmenter) 47 1 87.5 216 195
Segment #301 (Labeled Image Segmenter) 47 1 87.5 218 197
Segment #310 (Labeled Image Segmenter) 47 3 88.5 211 192
Segment #360 (Labeled Image Segmenter) 47 1 89.5 208 191
Segment #362 (Labeled Image Segmenter) 47 4 89.56221008 208.8542023 193.6849518
Segment #363 (Labeled Image Segmenter) 47 1 89.5 214 199
Segment #386 (Labeled Image Segmenter) 47 1 90.5 213 201
Segment #557 (Labeled Image Segmenter) 47 43 361.401886 203.4526672 201.9435272
Segment #590 (Labeled Image Segmenter) 47 32 363.2678833 206.9396057 200.0594482
Segment #618 (Labeled Image Segmenter) 47 2 365.5 207.5 193.5
Segment #621 (Labeled Image Segmenter) 47 1 365.5 210 198
Segment #623 (Labeled Image Segmenter) 47 2 365.5 211.5 200.5
Segment #635 (Labeled Image Segmenter) 47 1 366.5 207 191
Segment #641 (Labeled Image Segmenter) 47 4 367.5 211.5 192.5
Segment #647 (Labeled Image Segmenter) 47 1 368.5 215 196
Segment #659 (Labeled Image Segmenter) 47 7 369.4151001 217.5265045 193.9624939
Segment #670 (Labeled Image Segmenter) 47 1 371.5 223 194
Segment #671 (Labeled Image Segmenter) 47 1 371.5 225 196
Segment #684 (Labeled Image Segmenter) 47 1 373.5 227 192
Segment #686 (Labeled Image Segmenter) 47 9 373.4155884 233.513382 195.8200989
Segment #688 (Labeled Image Segmenter) 47 1 373.5 237 199
Segment #697 (Labeled Image Segmenter) 47 1 375.5 233 192
Segment #698 (Labeled Image Segmenter) 47 2 375.5 235 192.5
Segment #699 (Labeled Image Segmenter) 47 2 375.5 244.5 196.5
Segment #700 (Labeled Image Segmenter) 47 1 375.5 250 199
Segment #707 (Labeled Image Segmenter) 47 1 376.5 240 194
Segment #708 (Labeled Image Segmenter) 47 1 376.5 243 195
Segment #711 (Labeled Image Segmenter) 47 1 377.5 245 193
Segment #712 (Labeled Image Segmenter) 47 7 377.5 254.5296326 195.3819427
Segment #3381 (Labeled Image Segmenter) 47 13840 76.26931763 241.613739 199.6082764
Segment #3531 (Labeled Image Segmenter) 47 13819 379.3269958 241.6437988 199.7061615
Hi Maitham,
were you able to reconstruct the topic with the small object?
best regards,
Mark