- From: Mihail Bota <mbota@almaak-01.usc.edu>
- Date: Sat, 03 Mar 2007 15:39:27 -0800 (PST)
- To: William Bug <William.Bug@DrexelMed.edu>
- Cc: Alan Ruttenberg <alanruttenberg@gmail.com>, Nigam Shah <nigam@stanford.edu>, kc28 Cheung <kei.cheung@yale.edu>, June Kinoshita <junekino@media.mit.edu>, Gwen Wong <wonglabow@verizon.net>, Donald Doherty <donald.doherty@brainstage.com>, MaryAnn Martone <maryann@ncmir.ucsd.edu>, Luis Marenco <luis.marenco@yale.edu>, W3C HCLSIG hcls <public-semweb-lifesci@w3.org>
For the sake of completeness, Swanson lab did not define any nomenclature, or part of it for ABA. As I said previously, ABA nomenclature and its hierarchy are inspired from Swanson-2004. So, is exactly opposite. I am not sure whether ABA used primarily or solely Paxinos/Franklin mouse atlas. Regarding "cols G and H", I cannot say anything, because I haven't seen the spreadsheet and I don't know what a PK is. Thus, I don't know what "thalamus" ID is about in Bill's message. Anyway, the unique identification or regions in BAMS is made by integer ID's and not by abbreviations. Mihai On Sat, 3 Mar 2007, William Bug wrote: > Sorry, Alan - got swamped with BIRN Ontology & Mouse BIRN AHM mtg > preparations for next week. > > You are right - you & I reviewed details related to ABA image meta > data last weekend - NOT brain region level meta data. > > I'd bet a lot of what Nigam lays out below - RGB LUT values and PK - > is correct. > > > Region Abbrev (Cols B & C): > 'CNU' can be found in the Swanson (2004) XML file ("Cerebral > nuclei"). Despite the ABA atlas gray scale image plates having been > derived from the Franklin & Paxinos adult C57Bl/6 atlas, as Mihail > mentioned, the Swanson lab did some region classification for ABA, > and they lumped this at a higher level in a region they called > "Cerebral Nuclei" - though, again as Mihail points out, Striatum > immediately maps in rodent to a structure referred to as the > "Caudoputamen" (http://brancusi.usc.edu/bkms/brain/show-braing2.php? > aidi=129). Caudoputamen [very important for the PD use case] and > other structures in the base of the telencephalon are a part_of a > larger structure they've defined for ABA as "Cerebral Nuclei (CNU) > The one fly-in-the-ointment here is the phrase "...they've defined > for ABA...". This doesn't necessarily map to any of the other brain > region classification schemes/CVs used elsewhere - not a trivial > process - but not impossible - both the NN group and BIRN groups are > working on this - as is Mihail - as he mentioned). As Mihail points > out - and you can see in the XML files he distributes - it does link > into the vocabulary used in Swanson 1998/2004 for rat. It most > likely does not deterministically map to the CVs used for brain > region by GENSAT (believe that somehow derived from some combination > of NN and regions as given in the Franklin&Paxinos mouse atlas - > believe the GENSAT segmentation was performed by someone from George > Paxinos's lab who went to work with the Rockefeller GENSAT group). > SenseLab has much less brain region detail. It MAY be using the > Swanson nomenclature. Given SenseLab has just a subset of the > regions you'd find in an atlas, it's possible someone there at Yale > could fairly quickly provide a lookup table mapping their region > terms to one of the other atlases (Luis may even have done this > already in the context of some of the neuroinformatics repository > integration work he has done over the last several years). > > > Region color (Cols D, E, F): > All digital atlas have a color LUT for regions. These are generally > just 8-bit (only because few atlas projects have foreseen having the > expert personnel resources to manually segment > 256 regions) In the > atlases, the regions derive from very laborious manual segmentation > done in tools like AMIRA by specially trained, highly knowledgeable > neuroanatomists. The manual segmentation is performed on 2D > sections, assembled into 3D volumes, smoothed, then added to the 3D > atlas voxel data (many atlases are not actually TRUE 3D data sets - > e.g., the Paxinos atlas used at ABA - so the re-assembly, smoothing > and integration with voxels isn't required in that case). > Anyway - ABA is obviously being forward looking and using 24-bit > values for their region LUT. Besides, when using Paxinos, they are > GIVEN the region segmentation, so the manual effort is potentially > eliminated (though the only electronic version of the region > segmentation typically must be obtained through the atlas publisher - > Elsevier in this case - and generally all the regions for a given > Paxinos image (sagittal or coronal) are just lumped into a single, > bit-mapped file. This means you must take that bitmap, run > algorithms to identify the individual regions (usually based on color > - e.g., just as you see here, each region has a specified color in > the bit map). The isolated regions can then be converted to a > geometric object format (from simple point list on to quad-tree or > oct-tree) and this is then stored separately in a RDBMS. This is > EXACTLY what the SMART Atlas project in BIRN (from Maryann Martone's > NCMIR group at UCSD - source of CCDB, too) has done. This way, each > individual region is defined as a geometry in a specified coordinate > space AND - most importantly - can then be used to support SPATIAL > queries on the atlas (e.g., "Show me all the defined brain regions > that lie within this shape I just drew on image X that you've > registered to your atlas coordinate space). > > > Other Region numbers: > > A) Cols G & H > I would guess these are BOTH PKs of some sort as they both contain > rather small and unique integers. Given column G is listed in order, > I'd guess that is the ABA internal PK for that region. The other ID > is probably a cross-reference to another brain region classification > scheme. A search of the various atlas classifications on the > Mihail's BAMS site doesn't appear to provide such equivalent IDs. > I've searched in NN, but those IDs don't correspond either (e.g., the > Col H. for "Thalamus" - 351 - does not correspond to the NN ID for > "Thalamus" - 283). > One interesting note - if you sort the spreadsheet on Col H - you > will find the rows are ordered in nearly perfect alphabetical order > by brain region abbreviation. This indicates to me these Col H > values are likely to relate to IDs created for these regions by > Mihail/Swanson when they did this classification work for ABA. There > are no integer PKs given in the BAMS XML files from the Swanson lab > that match these numbers, so only Mihail can vet this hunch. I'd > guess they are expecting to use the "brain region abbreviation" as > their immutable, unique link. > > B) Col I: > Typically, the whole purpose of registering brain image stacks into > the coordinate space of a digital atlas (such as has been done for > the 20,000+ ABA image stacks for the individual, gene-specific, > GenePaint-ed brains) is so the expert segmented regions from the > digital atlas can be used to drive QUANTITATIVE ANALYSIS of the > registered image stacks in a consistent and comparable manner. Being > able to visualize the atlas regions overlayed onto individual images > from a given registered stack is useful for making qualitative > observations - or as a pedagogical aid - BUT it can't drive automated > analysis unless: > - the atlas comes with a coordinate system and the segmented brain > regions have been deterministically mapped into that space > - the image stacks have been registered to the same coordinate space. > In the case of the ABA, the atlas is the Franklin&Paxinos 2001 adult > C57Bl/6 brain atlas and the coordinate space is their interpretation > of stereotaxic coordinate mapping. The registration process has some > error (for ABA, I believe that is 300 microns [probably different for > in-plane registration - i.e., 2D to 2D alignment - vs. the third > dimension between images in a given dissection axis (i.e., coronal or > saggital for ABA)]). > SO - for Cols J,K,L, they likely refer to the location of the brain > regions in the coordinate space. In a true 3D atlas, all you'd have > to do is give 3D geometric definition of the region shape (e.g., as > an oct-tree), and give the location of the centroid for that shape in > the coordinate system. Since the F&P atlas is NOT a true 3D atlas > but rather a series of 2D images, you don't have a 3D geometric > definition of the region. With that in mind, the way to specify > WHERE in the atlas a given region lies is to give the FIRST and LAST > atlas image plate the extents of that region lie in when viewed along > a specific dissection axis. For very convoluted structures such as > the hippocampal formation, this can be a bit problematic to use > computationally, but it's usually sufficient for the types of tasks a > 2D atlas can support. > In terms of what this set up can support, it is likely one of the > things they are looking to do is to support users segmenting the gene- > specific images (GenePaint-ed images) then comparing those gene > specific segmentations to the brain segmentations. Given the limits > of the 2D realm, you can't really do true 3D volumetric > intersection. However, what you can do is determine to what extent > regions-of-interest (ROI) created by users to identify expression > patterns on a given GenePainted image overlap with the 2D sections > through the brain regions that appear on the corresponding, > registered Paxinos plate. You would essentially try to estimate an > intersection of the user drawn 2D ROIs with the 2D atlas region > shapes for each region that appears on that Paxinos plate. When > sorting those numbers by atlas brain region, you'd then go through > ALL the atlas images that contain a given region, and add up the > total intersection with the user drawn ROIs across all the images > from BRAIN X that user drew ROIs on. This would be normalized to the > total approx. pixel volume for that brain region across all the atlas > plates where it appears - resulting in an APPROXIMATE volume ratio of > a given gene stained for in BRAIN X with a given region defined in > the atlas. The large number - Col I - appears to scale with the > approximate size of the region - e.g., "Olfactory areas" is quite > large (838206), whereas one of the smaller regions included within > OLF is much smaller (Nucleus of the lateral olfactory tract [NLOT] - > 7407) - so I would guess this column represents that altas-defined > approx. region volume (i.e., sum of all the 2D areas defined for that > brain region across all the F&P atlas images). > > B) Cols J, K, L: > It's quite likely ABA calculated an approx. 3D location value for a > region probably truncated based on the existing locations of the > Paxinos plates within the stereotaxic coordinate space. Those > coordinates would be specified either with: > * a 2D coordinate location within a F&P atlas image plate (either > as unitless PIXELS or as stereotaxically-defined MICRONS) + a unique > ID for that F&P atlas image plate derived from a specific dissection > plane axis (e.g., F&P Coronal plate 23) > * a 3D coordinate location that somehow places some morphological > property of the region in the stereotaxic coordinate space - e.g. > front-upper-left point for the approx. 3D bounding box for that > region, centroid for the approx. 3D bounding box for that region, etc. > > That's all I have time for now. Must get back to meeting prep. It's > possible reading the ABA Nature paper from January would get you a > more specific answer - or - better yet - just drop an email to the > guy you spoke with at ABA. > > Hope that helps. > > Cheers, > Bill > > > On Mar 2, 2007, at 5:15 PM, Alan Ruttenberg wrote: > > > Don't recall doing this, though it's certainly possible that I've > > forgotten. > > Just to clarify, each of these lines is for a brain region, not for > > an image. > > If you want to do this later this evening with me, give me a call > > at home after about 10. > > -Alan > > > > On Mar 2, 2007, at 5:10 PM, William Bug wrote: > > > >> Alan, > >> > >> Didn't you and I review this already at the ABA site. > >> > >> All one would need to do is bring up one of these images at the > >> ABA site, go through the "noodling" we did, and look at the > >> corresponding entries in the spreadsheet to match up a "meaning" > >> to each column (probably nearly all those columns). > >> > >> Cheers, > >> Bill > >> > >> On Mar 2, 2007, at 2:15 PM, Nigam Shah wrote: > >> > >>>> BTW, if someone has a theory of what the other number in > >>>> ontology.xls are, I'm all ears. > >>> > >>> Okay, pure guesses: > >>> > >>> Line 4 = Cerebral > >>> cortex,CTX,CH,176,255,184,3, 85,4141526,61.647,29.999,33.711 > >>> > >>> 176,255,184 seem like RGB values (they all range from 2 to 255) for > >>> that region in the image. > >>> 3 is a serial number or internal id. > >>> 85 - no clue > >>> 4141526 - no clue > >>> 61.647,29.999,33.711 seem like 3D voxel coordinates. > >>> > >>> --Nigam. > >>> > >> > >> Bill Bug > >> Senior Research Analyst/Ontological Engineer > >> > >> Laboratory for Bioimaging & Anatomical Informatics > >> www.neuroterrain.org > >> Department of Neurobiology & Anatomy > >> Drexel University College of Medicine > >> 2900 Queen Lane > >> Philadelphia, PA 19129 > >> 215 991 8430 (ph) > >> 610 457 0443 (mobile) > >> 215 843 9367 (fax) > >> > >> > >> Please Note: I now have a new email - William.Bug@DrexelMed.edu > >> > >> > >> > >> > > > > Bill Bug > Senior Research Analyst/Ontological Engineer > > Laboratory for Bioimaging & Anatomical Informatics > www.neuroterrain.org > Department of Neurobiology & Anatomy > Drexel University College of Medicine > 2900 Queen Lane > Philadelphia, PA 19129 > 215 991 8430 (ph) > 610 457 0443 (mobile) > 215 843 9367 (fax) > > > Please Note: I now have a new email - William.Bug@DrexelMed.edu > > > > >
Received on Saturday, 3 March 2007 23:41:02 UTC